Method and apparatus for providing a pharmacokinetic drug dosing regiment

ABSTRACT

Systems and methods for providing a clotting factor VIII (CFVIII) dosing regimen include collecting two blood samples from a patient after an infusion of CFVIII and determining a CFVIII clearance based on the two blood samples, and determining if a patient has a half-life greater than a predetermined threshold. A pharmacokinetic (PK) profile of the patient is determined using a Bayesian model of pharmacokinetic profiles of sampled patients having similar body weight or age of the patient. A first weight is applied to the Bayesian model of pharmacokinetic profiles of sampled patients if the half-life of the patient is greater than the predetermined threshold, and a second weight, less than the first weight, is applied to the Bayesian model of pharmacokinetic profiles of sampled patients if the half-life of the patient is less than the predetermined threshold. A dosing regimen is determined for the patient based on the PK profile.

PRIORITY CLAIM

The present application claims priority to and the benefit of U.S.Provisional Patent Application No. 62/323,015, filed on Apr. 15, 2016,the entire content of which is incorporated herein by reference andrelied upon.

BACKGROUND

Clotting factor VIII is a blood-clotting protein that is activated inresponse to an injury or bleed. Individuals with relatively low levelsof clotting factor VIII are susceptible to internal or external episodesof prolonged bleeding resulting from an injury and/or spontaneousbleeding without a cause. While skin bleeds are not serious, internalbleeding of joints, muscles, and organs can cause permanent damage,disfigurement, or even death.

Patients with hemophilia A have a genetic deficiency that causes lowlevels of clotting factor VIII. The amount of clotting factor VIII in apatient is expressed as a percentage relative to a normal level.Patients with 5 to 40% of clotting factor VIII are considered to have amild form of hemophilia A while patients with 1 to 5% of clotting factorVIII are considered to have a moderate form of hemophilia A. Patientswith less than 1% of clotting factor VIII are considered to have asevere form of hemophilia A.

Treatment of patients with hemophilia A (or patients that otherwise havelow levels of clotting factor VIII) includes providing these patientswith periodic infusions of a clotting factor concentrate (e.g.,therapeutic plasma protein). The clotting factor concentrate acts as areplacement or supplement for the patient's natural occurring clottingfactor VIII. One example of such a therapeutic plasma protein is Shire'sADVATE drug. In some instances, patients receive the therapeutic plasmaprotein in response to having an uncontrolled internal bleed.Alternatively, patients may be prescribed a prophylactic treatmentregimen of the therapeutic plasma protein to reduce the possibility offuture bleeds. Oftentimes, this regimen requires that a patient visit ahealthcare provider and/or self-infuse the therapeutic plasma proteinthree or more times a week to receive treatments.

The goal of a treatment regimen is to schedule patient visits such thatthe clotting factor VIII, as provided by the therapeutic plasma protein,does not fall below a predetermined threshold, such as one percent (1%).However, the amount of therapeutic plasma protein needed in a patient isdependent upon the dosing amount and metabolism of the clotting factorVIII by the patient. Additionally, because there is a wide variabilityin the clotting factor VIII pharmacokinetic disposition in thepopulation, many patients may not be dosed properly to maintain theintended FVIII target trough across the dosing interval. Thus, it isnecessary to determine the individual patient's pharmacokinetic profileto ensure the proper dose is administered for the chosen time interval.

To prescribe a treatment regimen, currently a healthcare providerdetermines how an administered dose of a therapeutic plasma protein iseliminated from a patient over a treatment time to identify apharmacokinetic profile of the patient. Oftentimes the determination ofa patient's full pharmacokinetic profile requires ten or more blooddraws to determine a level or concentration of the therapeutic plasmaprotein within the patient at different times from initialadministration of the therapeutic plasma protein dose (e.g., determinehow the therapeutic plasma protein is eliminated over time). Thesemultiple blood draws require a patient to stay within a healthcarefacility for a prolonged duration or visit the healthcare facilitymultiple times. These multiple visits and/or multiple blood draws placeconsiderable stress on the patient and the healthcare facility.

To avoid any chance of a patient falling below a predeterminedthreshold, many healthcare providers design treatment regimens thatrequire patients to receive a therapeutic plasma protein infusion everyone, two, or three days in accordance with an approved product label. Anevery-one-day or every-two-day regimen places stress on patients byrequiring them to infuse relatively frequently. The every-one-day andevery-two-day regimens may also be unnecessary for some patients.However, the every-one-day and every-two-day regimens make it easier andmore practical for a healthcare provider to maintain higher therapeuticplasma protein levels in a patient above a specified peak therapeuticplasma protein level.

SUMMARY

An example system, method, and apparatus are disclosed that determine atherapeutic plasma protein dosing regimen for a patient. The examplesystem, method, and apparatus determine the dosing regimen using apharmacokinetic profile of the patient that is derived from apharmacokinetic model of a previously sampled patient population and/orindividual patient information. The pharmacokinetic profile of thepatient may be refined or modified based on previous therapeutic plasmaprotein treatments of the patient and/or patient specificcharacteristics such as age, body weight, other plasma protein levels,physical activity level, gender, disease state, etc. The system, method,and apparatus provide a graphical interface of the pharmacokineticprofile of the patient that enables a user (e.g., a health careprofessional) to adjust dosage, dosing interval, and a minimumacceptable concentration of the therapeutic plasma protein within thepatient to view how the dosing regimen changes. Such a configurationenables a healthcare provider to determine an optimal dosing regimenthat reduces (or prevents) a patient from risk of bleeds as a result ofhaving low levels of clotting factor VIII.

In an example embodiment, a method includes determining an estimatedpharmacokinetic profile of a patient using a Bayesian model ofpharmacokinetic profiles of sampled patients, the estimatedpharmacokinetic profile based upon at least one of a body weight or anage of the patient. The example method also includes determining a firstdosing regimen for a first specified dosing interval including (i) afirst dosage and (ii) a first therapeutic plasma protein level in thepatient over a time period based at least upon the estimatedpharmacokinetic profile and determining a second dosing regimen for asecond specified dosing interval including (i) a second dosage and (ii)a second therapeutic plasma protein level in the patient over the timeperiod based at least upon the estimated pharmacokinetic profile. Themethod further includes displaying the first dosing regimen and thesecond dosing regimen on a client device such that the first dosingregimen is displayed in conjunction with the second dosing regimen.

In another example embodiment, an apparatus includes a model generatorconfigured to create a Bayesian model of pharmacokinetic profiles ofsampled patients, the Bayesian model including a (i) therapeutic plasmaprotein clearance and (ii) a volume of distribution relationship for atherapeutic plasma protein based upon at least one of patient age orbody weight. The example apparatus also includes a pharmacokineticserver configured to determine an approximate pharmacokinetic profile ofa patient based upon the Bayesian model and at least one of an age ofthe patient or a body weight of the patient and determine a therapeuticplasma protein dosing regimen including a dosage and a therapeuticplasma protein level over a time period based upon the approximatepharmacokinetic profile of the patient. The pharmacokinetic server isalso configured to modify the therapeutic plasma protein dosing regimenin response to receiving a dosing interval for applying the dosage tothe patient and transmit the modified therapeutic plasma protein dosingregimen to a client device.

In yet another example embodiment, a machine-accessible device hasinstructions stored thereon that are configured, when executed, to causea machine to at least prompt a user to enter at least one of a patientbody weight or age and use a Bayesian model of pharmacokinetic profilesof sampled patients to determine an approximate pharmacokinetic profileof a patient based upon the Bayesian model and the at least one ofentered patient body weight or age, the Bayesian model including (i) atherapeutic plasma protein clearance and (ii) a volume of distributionrelationship for a therapeutic plasma protein based upon the at leastone of entered patient body weight or age. The example instructions alsocause the machine to determine a dosing regimen for the patient basedupon the approximate pharmacokinetic profile of the patient, the dosingregimen including a dosage and a dosage interval. The exampleinstructions further cause the machine to modify the dosing regimen inresponse to receiving another dosing interval for applying the dosage tothe patient and enable the dosing regimen and a time-varying therapeuticplasma protein level based on the dosing regimen to be displayed to auser.

Aspects of the subject matter described herein may be useful alone or incombination with one or more other aspect described herein. Withoutlimiting the foregoing description, in a first aspect of the presentdisclosure, a method for providing a therapeutic plasma protein dosingregimen includes determining, via a processor, an estimatedpharmacokinetic profile of a patient using a Bayesian model ofpharmacokinetic profiles of sampled patients, the estimatedpharmacokinetic profile based upon at least one of a body weight or anage of the patient, determining, via the processor, a first dosingregimen for a first specified dosing interval including (i) a firstdosage and (ii) a first therapeutic plasma protein level in the patientover a time period based at least upon the pharmacokinetic profile,determining, via the processor, a second dosing regimen for a secondspecified dosing interval including (i) a second dosage and (ii) asecond therapeutic plasma protein level in the patient over the timeperiod based at least upon the pharmacokinetic profile, and displayingthe first dosing regimen and the second dosing regimen on a clientdevice such that the first dosing regimen is displayed in conjunctionwith the second dosing regimen.

In accordance with a second aspect of the present disclosure, which maybe used in combination with the first aspect, the method furtherincludes adjusting, via the processor, the estimated pharmacokineticprofile of the patient based upon previous treatments of the patient.

In accordance with a third aspect of the present disclosure, which maybe used in combination with any one or more of the preceding aspects,the second specified dosing interval is longer than the first specifieddosing interval.

In accordance with a fourth aspect of the present disclosure, which maybe used in combination with any one or more of the preceding aspects,the first specified dosing interval is 48 hours and the second specifieddosing interval is 72 hours.

In accordance with a fifth aspect of the present disclosure, which maybe used in combination with any one or more of the preceding aspects,the minimum threshold level is less than 20%.

In accordance with a sixth aspect of the present disclosure, which maybe used in combination with any one or more of the preceding aspects,the first dosage is determined such that the first therapeutic plasmaprotein level in the patient over the time period does not fall belowthe minimum threshold level.

In accordance with a seventh aspect of the present disclosure, which maybe used in combination with any one or more of the preceding aspects,the first therapeutic plasma protein level in the patient is based uponat least one of a minimum threshold level, the first dosage, or thefirst specified dosing interval, and the second therapeutic plasmaprotein level in the patient is based upon at least one of the minimumthreshold level, the second dosage, or the second specified dosinginterval.

In accordance with an eighth aspect of the present disclosure, which maybe used in combination with any one or more of the preceding aspects,the Bayesian model includes a two-compartment model having a firstcompartment corresponding to a time to metabolize the therapeutic plasmaprotein and a second compartment corresponding to a dose for achieving acertain amount of the therapeutic plasma protein within the patient. Insome embodiments, the Bayesian model may mathematically describe apharmacokinetic disposition of clotting factor FVIII once administeredto a patient.

In accordance with a ninth aspect of the present disclosure, which maybe used in combination with any one or more of the preceding aspects, anapparatus for providing a therapeutic plasma protein dosing regimen to aclient device includes a model generator configured to create a Bayesianmodel of pharmacokinetic profiles of sampled patients, the Bayesianmodel including a (i) therapeutic plasma protein clearance and (ii) avolume of distribution relationship for a therapeutic plasma proteinbased upon at least one of patient age or body weight and apharmacokinetic server configured to determine an approximatepharmacokinetic profile of a patient based upon the Bayesian model andat least one of an age of the patient or a body weight of the patient,determine the therapeutic plasma protein dosing regimen including adosage and a therapeutic plasma protein level over a time period basedupon the approximate pharmacokinetic profile of the patient, modify thetherapeutic plasma protein dosing regimen in response to receiving adosing interval for applying the dosage to the patient, and transmit themodified therapeutic plasma protein dosing regimen to the client device.

In accordance with a tenth aspect of the present disclosure, which maybe used in combination with any one or more of the preceding aspects,the dosing interval is a two-day dosing interval, and wherein thepharmacokinetic server is configured to further modify the therapeuticplasma protein dosing regimen in response to receiving a three-daydosing interval in place of the two-day dosing interval.

In accordance with an eleventh aspect of the present disclosure, whichmay be used in combination with any one or more of the precedingaspects, the pharmacokinetic server is configured to transmit a drugdosing tool to the client device, the drug dosing tool being configuredto determine the therapeutic plasma protein dosing regimen and themodified therapeutic plasma protein dosing regimen.

In accordance with a twelfth aspect of the present disclosure, which maybe used in combination with any one or more of the preceding aspects,the pharmacokinetic server is further configured to modify thetherapeutic plasma protein dosing regimen based on daily activities ofthe patient.

In accordance with a thirteenth aspect of the present disclosure, whichmay be used in combination with any one or more of the precedingaspects, the pharmacokinetic server is further configured to transmitthe modified therapeutic plasma protein dosing regimen to an infusionpump for administering the therapeutic plasma protein to the patient. Inthis aspect and any other aspect, a physician, via the pharmacokineticserver, can locally or remotely control the infusion pump such that thepatient is only dosed (i.e., administered) with an amount of thetherapeutic plasma protein that is consistent with a current dosingregimen based on the pharmacokinetic profile of the patient.Additionally, the physician, via the drug dosing tool, can remotelymonitor and provide the patient with a renewed prescription of thetherapeutic plasma protein based on a currently an available quantity ofthe therapeutic.

In accordance with a fourteenth aspect of the present disclosure, whichmay be used in combination with any one or more of the precedingaspects, the approximate pharmacokinetic profile is a first approximatepharmacokinetic profile determined for a first therapeutic plasmaprotein treatment of the patient, and wherein the pharmacokinetic serveris further configured to determine a second approximate pharmacokineticprofile for the patient for a second therapeutic plasma proteintreatment of the patient based on the modified therapeutic plasmaprotein dosing regimen.

In accordance with a fifteenth aspect of the present disclosure, whichmay be used in combination with any one or more of the precedingaspects, the volume of distribution relationship for the therapeuticplasma protein is a relationship for at least one of clotting factorVIII and modified forms of clotting factor VIII.

In accordance with a sixteenth aspect of the present disclosure, whichmay be used in combination with any one or more of the precedingaspects, a machine-accessible device has instructions stored thereonthat are configured, when executed, to cause a machine to at leastprompt a user to enter at least one of a patient body weight or age, usea Bayesian model of pharmacokinetic profiles of sampled patients todetermine an approximate pharmacokinetic profile of a patient based uponthe Bayesian model and the at least one of entered patient body weightor age, the Bayesian model including (i) a therapeutic plasma proteinclearance and (ii) a volume of distribution relationship for atherapeutic plasma protein based upon the at least one of enteredpatient body weight or age, determine a dosing regimen for the patientbased upon the approximate pharmacokinetic profile of the patient, thedosing regimen including a dosage and a dosage interval, modify thedosing regimen in response to receiving another dosing interval forapplying the dosage to the patient, and enable the dosing regimen and atime-varying therapeutic plasma protein level based on the dosingregimen to be displayed to a user.

In accordance with a seventeenth aspect of the present disclosure, whichmay be used in combination with any one or more of the precedingaspects, the machine-accessible device further comprises instructionsstored thereon that are configured when executed to cause the machine todetermine a first dosing regimen for a two-day dosing interval,determine a second dosing regimen for a three-day dosing interval, andenable the display of the first dosing regimen in conjunction with thesecond dosing regimen.

In accordance with an eighteenth aspect of the present disclosure, whichmay be used in combination with any one or more of the precedingaspects, the machine-accessible device further comprises instructionsstored thereon that are configured when executed to cause the machine todisplay a graphical representation of a time-varying amount of thetherapeutic plasma protein within the patient, including at least oneindication of a dose of the therapeutic plasma protein being provided tothe patient.

In accordance with a nineteenth aspect of the present disclosure, whichmay be used in combination with any one or more of the precedingaspects, the machine-accessible device further comprises instructionsstored thereon that are configured when executed to cause the machine todisplay a graphical feature than enables a user to change at least oneof (i) a minimum concentration threshold, (ii) the dosage interval, or(iii) the dosage of the therapeutic plasma protein.

In accordance with a twentieth aspect of the present disclosure, whichmay be used in combination with any one or more of the precedingaspects, the machine-accessible device further comprises instructionsstored thereon that are configured when executed to cause the machine tomodify the dosing regimen in response to receiving a change of any oneof the items (i), (ii), or (iii).

In accordance with a twenty-first aspect of the present disclosure,which may be used in combination with any one or more of the precedingaspects, the machine-accessible device further comprises instructionsstored thereon that are configured when executed to cause the machine todisplay a graphical representation of a change in the amount of thetherapeutic plasma protein within the patient over time based on thechange of any one of the items (i), (ii), or (iii).

In accordance with a twenty-second aspect of the present disclosure,which may be used in combination with any one or more of the precedingaspects, the machine-accessible device further comprises instructionsstored thereon that are configured when executed to cause the machine toreceive a minimum concentration threshold and to display an amount oftime the therapeutic plasma protein level is below the minimumconcentration threshold.

In accordance with a twenty-third aspect of the present disclosure,which may be used in combination with any one or more of the precedingaspects, the machine-accessible device further comprises instructionsstored thereon that are configured when executed to cause the machine toreceive patient measurement blood laboratory data including aconcentration of the therapeutic plasma protein within the patient aftera time from when the therapeutic plasma protein was administered to thepatient and modify the approximate pharmacokinetic profile based on thepatient measurement blood laboratory data.

In accordance with a twenty-fourth aspect of the present disclosure, anyof the structure and functionality illustrated and described inconnection with FIGS. 1 to 31 may be used in combination with any of thestructure and functionality illustrated and described in connection withany of the other of FIGS. 1 to 31 and with any one or more of thepreceding aspects.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 shows a diagram of an example pharmacokinetic drug dosingenvironment, according to an example embodiment of the presentdisclosure.

FIG. 2 shows a diagram of patient sample data for a number of patientswith hemophilia A, according to an example embodiment of the presentdisclosure.

FIGS. 3 to 13 show diagram that include example user interfaces providedby the drug dosing tool of FIG. 1 to determine a dosing recommendationand estimated pharmacokinetic profile for a specific patient, accordingto an example embodiment of the present disclosure.

FIGS. 14 to 18 show diagrams that include user interfaces provided bythe drug dosing tool of FIG. 1 in a marketing tool embodiment, accordingto an example embodiment of the present disclosure.

FIGS. 19 and 20 show diagrams that include a flow diagram illustratingan example procedure to determine a dosing regimen, according to anexample embodiment of the present disclosure.

FIGS. 21 and 22 show diagrams that include an example embodiment where apharmacokinetic profile for a specific patient is adjusted based onactivity level.

FIGS. 23 to 30 show diagrams of tables and graphs that correlate aconcentration of administered therapeutic plasma protein with bleed riskfor different patients, according to an example embodiment of thepresent disclosure.

FIG. 31 shows a detailed block diagram of an example model generator,server, and/or client device of the pharmacokinetic drug dosingenvironment of FIG. 1, according to an example embodiment of the presentdisclosure.

FIG. 32 shows a diagram of an amount of time in which clotting factorVIII was above a 1 IU/dL threshold for a sample of patients with longerhalf-lives.

FIG. 33 shows a diagram of an amount of time in which clotting factorVIII was above a 1 IU/dL threshold for a sample of patients with shorterhalf-lives (i.e., half-lives less than 12 hours).

FIG. 34 shows a diagram of clotting factor FVIII clearance for 27different patients over time.

FIG. 35 shows a diagram of an amount of time in which clotting factorVIII was above a 1 IU/dL threshold for patients in which a pre-fittingstep was used.

DETAILED DESCRIPTION

The present disclosure relates in general to a method, system, andapparatus to provide a drug dosing regimen, and in particular, toprovide a pharmacokinetic drug dosing regimen based upon a model ofpharmacokinetic profiles of sampled patients. The pharmacokinetic drugdosing regimen described herein provides a cost-effective use oftherapeutic plasma protein, which may be tailored to an individualpatient. As such, the example pharmacokinetic drug dosing regimendescribed herein provides healthcare providers with a tool that enablesrelatively quick and accurate patient dosing recommendations withouthaving to determine a patient specific pharmacokinetic profile based(solely) upon blood testing. The disclosure also contemplates, clottingfactor FVIII products that are modified to extend residence mean timesin a patient beyond that of native FVIII through, for example, the useof water soluble proteins or FC fusion technology, and dosingschemes/intervals longer than three days.

Presently, healthcare providers formulate a treatment regimen for apatient with low levels of naturally occurring clotting factor VIII bydetermining a patient specific pharmacokinetic profile to identify howthe patient metabolizes a therapeutic plasma protein over time. Todetermine a patient's pharmacokinetic profile, a healthcare providerperforms an initial baseline blood draw before a patient is administereda therapeutic plasma protein. This baseline blood draw is used todetermine the amount of naturally occurring clotting factor VIII in thebody. The healthcare provider then administers the therapeutic plasmaprotein and performs three or more blood draws over a 48-hourpost-treatment period. Over this time, the patient metabolizes thetherapeutic plasma protein such that the concentration of clottingfactor VIII within the patient returns to the patient's own naturallyoccurring level. The healthcare provider analyzes the patient's drawnblood via laboratory analyzers to determine the amount of clottingfactor VIII within the patient at each blood draw. This analyzed bloodlaboratory data enables the healthcare provider to determine how quicklya patient metabolizes the therapeutic plasma protein.

As a general rule, most healthcare providers set a target (widelyaccepted) threshold such that the clotting factor VIII within a patientdoes not fall below 1% (i.e., 11U/dL). Patients with less than 1% ofclotting factor VIII are considered susceptible to uncontrolled orspontaneous bleeds. While this approach works some of the time, manypatients have daily, weekly, or even monthly variances in theirmetabolism and/or tendencies to bleed, and may need different clottingfactor FVIII levels to remain bleed free. These variances are oftentimesrelated to patient body weight, age, joint health, and physical activitylevel. The dosing regimen determined for the patient usually does notaccount for these variances, which potentially leaves the patientexposed to bleeds if the clotting factor VIII falls below the generallyaccepted 1% natural baseline threshold, and/or is lower than needed toprevent bleeds during periods of higher risk/physical activity.

The example method, system, and apparatus disclosed herein account forpatient pharmacokinetic variance by creating individual patient profilesbased not only on the patient's own intensive pharmacokinetic profiling,but rather a (Bayesian) model that uses pharmacokinetic profiles of aset of sample representative patients and/or and a limited number ofpatient blood sample data points in conjunction with minimal patientinformation. The example method, system, and apparatus disclosed hereinenable a healthcare provider to refine the model based on a patient'sprevious treatments and/or an activity level of the patient. Such aconfiguration enables healthcare providers to create individualizeddosing regimens based on knowledge of a population of sampled patientsthat have similar characteristics as the patient undergoing treatment,thereby reducing the effects of individual pharmacokinetic variance ofthe patient and reducing (or preventing) the number of bleedsexperienced by the patient while on prophylaxis.

The example disclosure includes two primary embodiments. A first primaryembodiment includes a drug dosing tool that uses previously collectedpatient data to establish one or more pharmacokinetic models. Theexample method, system, and apparatus use this model to determine how atherapeutic plasma protein changes over time in a patient based upon thepatient's physical attributes (e.g., age, body weight, gender, activitylevel, endogenous clotting factor VIII level, etc.) and previous dosingtreatments. A healthcare provider may use the model to determine a drugdosage and dosing interval for the patient.

A second primary embodiment includes a drug dosing tool, such as anapplication (“App”) operating on a mobile computer (e.g., a smart phoneor a tablet computer). The application is configured to enable a user(e.g., a drug sales representative) to provide healthcare providers witha graphical interface that displays how a particular therapeutic plasmaprotein (e.g., a clotting factor VIII such as Shire's ADVATE) performsunder different conditions. The example pharmacokinetic drug tool ofthis second embodiment uses a pharmacokinetic model of sampled patientsto enable the user to highlight the benefits of using, for example, anevery-three-day dosing scheme, an every-four-day dosing scheme, anevery-five-day dosing scheme, etc. instead of an every-one-day or anevery-two-day dosing scheme for therapeutic plasma protein. The drugtool uses relationships between therapeutic plasma proteinconcentrations, therapeutic plasma protein dosage levels, therapeuticplasma protein dosage times, and patient parameters to calculate how thetherapeutic plasma protein concentration changes over time for atheoretical patient.

As used herein, the term “clotting factor VIII”, “FVIII”, or “rAHF”refers to any FVIII molecule that has at least a portion of the B domainintact, and which exhibits biological activity that is associated withnative FVIII. In one embodiment of the disclosure, the FVIII molecule isfull-length FVIII. The FVIII molecule is a protein that is encoded byDNA sequences capable of hybridizing to DNA encoding FVIII:C. Such aprotein may contain amino acid deletions at various sites between orwithin the domains A1-A2-B-A3-C1-C2. The FVIII molecule may also be ananalog of native clotting factor FVIII, wherein one or more amino acidresidues have been replaced by site-directed mutagenesis.

The term “recombinant Factor VIII” (rFVIII) may include any rFVIII,heterologous or naturally occurring, obtained via recombinant DNAtechnology, or a biologically active derivative thereof. As used herein,“endogenous FVIII” includes FVIII which originates from a mammalintended to receive treatment. The term also includes FVIII transcribedfrom a transgene or any other foreign DNA present in the mammal. As usedherein, “exogenous FVIII” or therapeutic plasma protein includesclotting factor FVIII that does not originate from a mammal.

The FVIII molecule exists naturally and in therapeutic preparations as aheterogeneous distribution of polypeptides arising from a single geneproduct. The term “clotting factor VIII” as used herein refers to allsuch polypeptides, whether derived from blood plasma or produced throughthe use of recombinant DNA techniques and includes, but is not limitedto FVIII mimetics, fc-FVIII conjugates, FVIII chemically modified withwater soluble polymers, and other forms or derivatives of FVIII.Commercially available examples of therapeutic preparations containingFVIII include those sold under the trade names of ADVATE, HEMOFIL M, andRECOMBINATE (available from Shire PLC, Dublin, Ireland). Otherpreparations comprise primarily a single subpopulation of FVIIImolecules, which lack the B domain portion of the molecule.

The FVIII molecules useful for the present disclosure include afull-length protein, precursors of the protein, biologically active orfunctional subunits or fragments of the protein, and/or functionalderivatives thereof, as well as variants thereof as described hereinbelow. Reference to clotting factor FVIII is meant to include allpotential forms of such proteins and wherein each of the forms of FVIIIhas at least a portion or all of the native B domain sequence intact.

“Dosing interval,” as used herein, means an amount of time that elapsesbetween multiple doses being administered to a patient. The dosinginterval for administering a therapeutic plasma protein includingclotting factor VIII may be at least about every one, two, three, four,five, six, seven, eight, nine, ten, eleven, twelve, thirteen, orfourteen days or longer. The dosing interval may change based onchanging conditions/characteristics of a patient, changes to a minimallyacceptable (e.g., target trough) concentration of the therapeutic plasmaprotein within a patient, and/or changes to a dosage.

Pharmacokinetic Drug Dosing Environment

FIG. 1 shows a diagram of an example pharmacokinetic drug dosingenvironment 100 that may implemented in either one or both of theembodiments described above. The environment 100 includes a modelgenerator 102 that is configured to generate one or more patientpharmacokinetic models 106 based upon sampled patient data 104. Theenvironment 100 also includes a pharmacokinetic (“PK”) server 108 thatis configured to provide patients, healthcare providers, and/or salesrepresentatives with a graphical pharmacokinetic drug dosing tool 110based upon the one or more pharmacokinetic models 106. In theillustrated embodiment, the PK server 108 transmits the tool 110 toclient devices 112 via a network 114 (e.g., an Internet). In otherembodiments, the PK server 108 hosts the tool 110, which is accessibleby the client devices 112. In these other embodiments, the PK server 108may include a single server, or alternatively, may be distributed withina cloud computing framework.

The example PK server 108 and/or the model generator 102 may becommunicatively coupled to a database 116 configured to store thepatient pharmacokinetic models 106. The database 116 may include anytype of computer-readable medium, including RAM, ROM, flash memory,magnetic or optical disks, optical memory, or other storage medium. Theexample database 116 may also store information generated in response tousers using the tool 110 including, for example, patient information,dosing regimens, etc. In some instances, the database 116 may be managedby a separate third-party storage provider.

In some instances, the PK server 108 and/or the model generator 102 maybe provided by the same server and/or processor and/or operated by thesame entity. In these instances, the functionality of the modelgenerator 102 may operate in conjunction with the functionality of thePK server 108. For instance, the model generator 102 may periodicallyupdate pharmacokinetic models with therapeutic plasma protein dosinginformation and/or patient information received in the PK server 108 viathe tool 110.

The example client devices 112 a, 112 b, and/or 112 c may include anydevice capable of displaying or otherwise operating the tool 110.Examples of the client devices 112 include a smartphone, a tablecomputer, a laptop computer, a desktop computer, a workstation, aserver, a processor, smart eyewear, a smart watch, etc. In someinstances the tool 110 may be installed on the client device 112. Inother instances, the tool 110 provides an interface (e.g., a webbrowser) to functionality configured to reside at the PK server 108. Inthese instances, the PK server 108 may include one or more applicationprogrammable interfaces (“APIs”) configured to enable the tool 110 toaccess the desired data and/or functionality.

Model Generator

In the embodiments described herein, a pharmacokinetic model is used toestimate or approximate pharmacokinetic profiles of patients becauseprecise patient-specific pharmacokinetic profiles are relatively complexor difficult to determine without extensive blood draws to determineclotting factor VIII in circulation. For instance, current methods todetermine a patient-specific pharmacokinetic profile for hemophilia Ainclude performing multiple blood tests. These blood tests includeperforming an initial blood draw to determine a clotting factor VIIIbaseline in a patient. Then, after therapeutic plasma protein isadministered, ten to twelve or more blood draws may be performed over a48 to 72 hour post-infusion period. As can be appreciated, such aprocedure is especially taxing on a patient, healthcare provider, andlab because of the numerous separate blood draws. Accordingly, theexample model generator 102 is configured to generate relativelyaccurate pharmacokinetic models based upon a sample of patients withvarying ages, body weights, genders, and activity levels. These modelsare then used to determine or approximate a pharmacokinetic profile of apatient without having to subject a patient to all of the blood drawsand subsequent analysis.

In an embodiment, the pharmacokinetic models 106 are determined usingpatient samples 104 selected from one or more sets of patient data. Thepatient samples 104 may be, for example, selected among patients whohave already been subscribed a therapeutic dosing regimen using theabove described blood draw procedure. The patient samples 104 may alsoinclude patients specifically selected to go through the blood drawprocedure for the purpose of creating the models. The patient samples104 may include patients from one hospital or medical system and/orpatients associated from multiple hospitals, medical systems, geographicregions, etc.

The patient samples 104 include data for patients of varying ages, bodyweights (or body mass index (“BMI”), medical conditions, clinicallaboratory data, genders, and/or activity levels. In the exampledescribed herein, sample patient ages vary between 2 and 100 years ofage. In some embodiments, the data for the patients may be separatedinto children and adult age brackets such that a separate model isgenerated for each bracket. The patient data may additionally oralternatively be partitioned based on body weight, gender, and/oractivity level.

As mentioned, the example patient samples 104 include a determination ofclotting factor VIII before therapeutic plasma protein is infused intothe patients. Then, post infusion blood samples are collected from eachpatient after certain durations of time. It should be appreciated thatin other examples, the blood samples may be collected at different timesand/or the number of blood samples collected may be fewer or greater.For instance, fewer blood samples may be collected from children.

FIG. 2 shows a diagram of graph 200 including patient sample data 104for one-hundred, fifty-two patients with hemophilia A. The sample data104 is shown as a level of clotting factor VIII in international units(“IU”) per deciliter (“dl”). The samples were collected at pre-infusion(shown at time 0) and post-infusion at intervals of 15 minutes, 30minutes, 1 hour, 3 hours, 6 hours, 9 hours, 24 hours, 28 hours, 32hours, and 48 hours. It should be appreciated that the amount of theclotting factor VIII provided by the therapeutic plasma protein in thepatient decreases over time as the patients metabolize the infusedtherapeutic plasma protein.

The example model generator 102 creates a pharmacokinetic patient modelby performing a Bayesian analysis that uses previous knowledge ofclotting factor VIII in the sampled patients over time after an infusionof the therapeutic plasma protein. In some instances, the modelgenerator 102 is configured to analyze each patient's sampled dosinghistory in conjunction with pre-infusion clotting factor VIII levels, sothat washout data is not needed to construct the pharmacokinetic models106. In other embodiments, the model generator 102 may use patientwashout data in conjunction with the post-infusion clotting factor VIIIlevels to create one or more pharmacokinetic models 106. Patient washoutdata corresponds to a baseline where the patient does not include thetherapeutic plasma protein in their system.

The example model generator 102 creates the one or more pharmacokineticmodels 106 using, for example, the patient sample data shown in thegraph 200. The model generator 102 may combine the individual patientsamples 104 into one or more population profiles (e.g., age sets, bodyweight sets, activity level sets, endogenous clotting factor VIII level,etc.), which is then used as a basis for the respective pharmacokineticmodel 106. For instance, the model generator 102 may group the patientsamples 104 for different ages, body weights, and/or activity levelsinto different sets. The model generator 102 then performs covariate andstatistical modeling on the grouped patient samples 104 of each set tocreate a population pharmacokinetic model 106 for that set, as describedin a white paper titled “Population pharmacokinetics of recombinantfactor VIII—the relationships of pharmacokinetics to age and bodyweight”, by Björkman et al., the entirety of which is incorporatedherein by reference. It should be appreciated however, that the modelgenerator 102 may model the sampled data 104 using other Bayesiananalysis techniques (e.g., a naive Bayes classifier).

In the illustrated example, the covariate model used by the modelgenerator 102 determines relationships between pharmacokineticparameters (e.g., how quickly therapeutic plasma protein is metabolized,endogenous clotting factor VIII level, etc.) and patient characteristics(e.g., age, body weight, clinical laboratory data, gender, activitylevel, etc.). The model generator 102 uses a statistical model todetermine variance in pharmacokinetic parameters among the sampledpatients in addition to residual variance as a result of biologicalvariability between patients, measurement errors, and errors within thefit of the sampled data 104 to the pharmacokinetic model.

The example model generator 102 is configured to perform the covariateand statistical modeling using non-linear mixed effects modeling with afirst-order integral approximation method, as provided in SAS® software(NLMIXED procedure). In the illustrated example, the model generator 102uses a two-compartment model. In other examples, the model generator 102may use a single compartment model or three or more compartment models.In the illustrated two-compartment example, the first compartmentincludes pharmacokinetic parameters of clearance (“CL”) and volume ofdistribution (V1).

CL refers to the amount of time for a patient to metabolize thetherapeutic plasma protein in milliliters (“mL”) per hour per kilogram(“kg”). In other words, clearance is a measure of a rate at which atherapeutic plasma protein is removed or eliminated from a patient. Themodel generator 102 uses example equation (1) to determine CL, where BWdenotes body weight, i denotes the specific sampled patient, and denotesstatistical inter-patient variability.

$\begin{matrix}{{C{L_{i}\left( {{mL}\text{/}h} \right)}} = {193^{*}{\left( \frac{{BW}_{i}}{56} \right)^{080}}^{*}\left( {1 - {0.0045^{*}\left( {{Age}_{i} - 22} \right)}} \right)^{*}{\exp \left( \eta_{i}^{CL} \right)}}} & (1)\end{matrix}$

V1 refers to a theoretical volume that the therapeutic plasma proteinwould have to occupy to provide the same concentration as it iscurrently in a patient's blood. This theoretical volume provides anestimation for a dose to achieve a certain clotting factor VIII level.The model generator 102 uses example equation (2) to determine V1. Inthe example described herein, V1 is about 0.04 L/kg.

$\begin{matrix}{{V\; 1_{i}(L)} = {{2.2}2^{*}{\left( \frac{BW_{i}}{56} \right)^{0.95}}^{*}{\exp \left( \eta_{i}^{V\; 1} \right)}}} & (2)\end{matrix}$

The second component of the illustrated model includes aninter-compartmental clearance (“Q”) and a second volume of distribution(“V2”), which does not account for inter-patient variability. The modelgenerator 102 uses example equation (3) to determine Q and equation (4)to determine V2. The inter-compartmental clearance Q is used inconjunction with clearance CL to determine a scaling relation of thesecond volume of distribution V2 to the first volume of distribution V1.In this example, the inter-compartmental clearance Q is notsignificantly related to body weight, indicating that V1 and V2 arecumulative for determining a volume of distribution at steady state. Inother words, the total volume of distribution is determined by adding V1and V2. In one implementation, the average total volume of distributionof the patient samples was found to be about 0.053 L/kg.

$\begin{matrix}{{Q_{i}\left( {{mL}\text{/}h} \right)} = 147} & (3) \\{{V\; 2_{i}(L)} = {{0.7}3^{*}\left( \frac{{BW}_{i}}{56} \right)^{{0.7}6}}} & (4)\end{matrix}$

After generating the model 106 provided by example equations (1) to (4)above, the example model generator 102 may verify the model bydetermining individual values for CL, Q, V1, V2, and V1+V2 for eachsampled patient and comparing the results to the model. Such acomparison provides an indication as to the accuracy of the model. Insome examples, the model generator 102 may determine a statisticaldistribution of the sampled patient data to determine whether the modelis accurate. In instances in which the model does not appear to beaccurate, the model generator 102 may compile additional patient samples104 and/or perform other modeling techniques.

Responsive to creating one or more pharmacokinetic models 106, the modelgenerator 102 provides the pharmacokinetic model(s) 106 to the PK server108. The transmission may be over a private network, such as a localarea network, or over a public network, such as an Internet. The modelgenerator 102 may also store the models 106 to the database 116, whichis also accessible by the PK server 108 via one or more interfaces. Inother instances, the model generator 102 may be integrated with the PKserver 108.

In addition to providing the pharmacokinetic models 106 based uponequations (1) to (4) above as applied to samples of random patients, theexample model generator 102 may refine the models for each patient whosetherapeutic plasma protein dosing is calculated using the drug dosingtool. For instance, the PK server 108 may receive patient specificinformation including, body weight, age, gender, endogenous clottingfactor VIII level, and dosing level for previous treatments. The modelgenerator 102 uses the previous treatment information (e.g., dosingamounts, intervals, etc.) to refine or adjust the model such that dosingrecommendations and a pharmacokinetic profile are more aligned to thespecific patient but still account for potential patient variance. Themodel generator 102 transmits the patient-specific model to the PKserver 108.

Alternatively, the PK server 108 may be configured to createpatient-specific models using the pharmacokinetic model 106 provided bythe model generator 102 to account for the patient-specificpharmacokinetic variance. In this manner, one or more base models 106are refined or adjusted by the PK server 108 responsive to receivingprevious treatment information for a specific patient. The PK server 108may be configured to store the patient-specific model to the database116 for subsequent uses by the same healthcare provider or otherhealthcare providers.

In yet other embodiments, the example tool 110 may be configured toadjust or refine a pharmacokinetic model based upon patient-specifictreatment information. For instance, the tool 110 may include fields fora user to provide previous treatment information. The example tool 110uses this previous treatment information when determining apharmacokinetic profile and dosing recommendations for a patient.Additionally or alternatively, the tool 110 may use treatmentinformation from multiple patients to refine and/or adjust the model106.

Patient-Specific Tool Embodiment

As discussed above, the PK server 108 can be configured to providedifferent embodiments of the drug dosing tool 110. FIGS. 3 to 13 includediagrams of example user interfaces provided by the drug dosing tool 110to determine a dosing regimen and estimated/approximate pharmacokineticprofile for a specific patient using one or more pharmacokinetic models106. It should be appreciated that the user interfaces may be modifiedin appearance and/or function based upon the configuration of the drugdosing tool 110. For instance, the graphical elements of the userinterfaces may be modified based upon a type of client device 112 (e.g.,a smart phone display, a tablet display, a personal computer display).

FIG. 3 includes a diagram of a user interface 300 that includes userregistration fields to enable a healthcare provider to access the drugdosing tool 110. The interface 300 includes data fields for userinformation (e.g., name, practice, address, contact information). Inaddition, the user interface 300 includes a field for a drug enforcementadministration (“DEA”) number, which is used by the PK server 108 tovalidate that the user is an authorized healthcare professional. Ininstances in which a healthcare professional does not have a DEA number,the professional may contact customer support to manually setup anaccount to use the tool 110.

Responsive to receiving the user-provided information in FIG. 3(including a proper DEA number), the example PK server 108 is configuredin the illustrated embodiment to create a user account, which includes auser dashboard. FIG. 4 includes a diagram of user interface 400 for apatient information portion of the dashboard. The user interface 400provides user management of patients under care of the user. A user usesthe user interface 400 to add a new patient, reactivate a currentpatient, open a report providing details regarding previous treatments(including previous determined pharmacokinetic profile and dosingrecommendation), or open a report of patient information. To add apatient, drug dosing tool 110 may provide another user interface thatprompts a user for patient information including name, address,insurance information, age, gender, body weight (or BMI), medicalconditions, clinical laboratory data, etc.

For any patient, the drug dosing tool 110 enables a user to determine anestimated/approximate pharmacokinetic profile and dosing recommendation.FIG. 5 includes a diagram of a user interface 500 associated with a newpatient visit. In this illustrated example, user interface 500 includesfields for patient information regarding the infusion of therapeuticplasma protein. In instances in which the patient is already registeredwith the tool 110, at least some of the fields may be pre-populated.Additionally, the ‘Dose for PK infusion’ field may be populated by thetool 110 responsive to the user progressing through the steps todetermine an estimated pharmacokinetic profile and dosing recommendationfor the patient.

The example drug dosing tool 110 may also be configured to warn a userif information provided exceeds a predetermined threshold. For example,the tool 110 may be configured to provide a warning message if thepre-infusion level exceeds 20 IU/kg. This warning provides an indicationto a user that the entered value is not typical for that field. However,a user may nevertheless continue to use the tool 110 with theinformation that caused the warning to be generated. Alternatively, thetool 110 may be configured to only accept information within thepredetermined range.

After providing a patient name, body weight, birth date, infusion date,and washout or pre-infusion level information, the example drug dosingtool 110 prompts a user to progress to the next step. FIG. 6 includes adiagram of a user interface 600 that is displayed subsequent to a user'sprovision of information into the user interface 500 of FIG. 5.

The example user interface 600 provides a review of previous patienttreatments and/or samples including pre-infusion (or washout)information and dosage (i.e., PK Infusion). A user can select to use thedata from one or more previous treatments and/or samples with the tool110 to refine or adjust the pharmacokinetic model 106 for a patient. Auser makes this selection by toggling the ‘On/Off’ buttons on theright-hand side of the interface 600. For instance, a user maydeactivate previous treatments and/or samples that occurred over threeyears in the past. As a result of this selection, the tool 110 only usesthe activated previous treatments and/or samples in refining thepharmacokinetic model 106. This configuration of the tool 110 therebyenables a user to refine a pharmacokinetic model as desired using onlyspecified previous patient treatments and/or samples. In some instances,the user may select to deactivate all previous treatments and/orsamples, thereby causing the tool 110 to use the pharmacokinetic model106 as provided by the model generator 102.

In the illustrated embodiment, three patient samples are shown for atreatment with a therapeutic plasma protein. Each of the samplescorresponds to a blood draw of the patient at a time from an infusiontreatment of the therapeutic plasma protein. For instance, the firstsample was collected 6 hours after the infusion, the second sample wascollected 24 hours after the infusion, and the third sample wascollected 30 hours after the infusion. The sample information includes adetermination of a concentration of clotting factor VIII within thepatient's blood at the time the sample was collected. It should beappreciated that the use of the pharmacokinetic model 106 in conjunctionwith certain selected patient samples may refine a determined patientpharmacokinetic profile to be specific for a patient while alsocompensating for patient variation common within a sampled population.

After selecting which treatments and/or samples are to be includedwithin pharmacokinetic model 106, the drug dosing tool 110 prompts auser to select a ‘Next Step’ button, causing the example tool 110 todisplay user interface 700 of FIG. 7. The example user interface 700provides a review of which previous treatments and/or samples are to beincluded in the determination of the estimated pharmacokinetic profileand dosing recommendation for the patient. The selected previoustreatments and/or samples may be used to provide a body weight to adosing regimen based upon previous provided doses. The user interface700 prompts the user to select the ‘Calculate’ button to cause the drugdosing tool 110 (or the PK server 108) to apply the patient specificinformation to the pharmacokinetic model 106 to determine an estimatedor approximate pharmacokinetic profile and dosing recommendation for thepatient. In some instances, the tool 110 may not make the ‘Calculate’button available until a user has provided at least a predeterminednumber of (e.g., three) previous treatments and/or samples to ensurethat the resulting determination is more specific to the patient. Itshould be appreciated that the tool 110 and/or the PK server 108 selectsa pharmacokinetic model of available pharmacokinetic models that bestmatches the patient information provided within the user interface 500and/or other user interfaces that prompt a user for patient-specificinformation. For instance, the pharmacokinetic model may be selectedbased on a patient's age, body weight, gender, and/or activity level.

FIG. 8 includes a diagram of the user interface 700 of FIG. 7, which nowdisplays the determined pharmacokinetic profile of the patient aftercalculation by the tool 110 and/or the PK server 108. The ‘Theoretical’fields correspond to data that is based solely on the pharmacokineticmodel 106 without the previous patient treatments and/or samples. The‘Adjusted’ fields correspond to pharmacokinetic profile data specific tothe patient based upon the pharmacokinetic model 106 adjusted with theprevious treatment and/or sample information. The ‘Offset’ fieldscorrespond to differences between the respective ‘Theoretical’ and‘Adjusted’ fields. In the illustrated example, the pharmacokineticprofile data includes a clearance of the therapeutic plasma protein,volume of distribution (vdBeta), maximum concentration that thetherapeutic plasma protein may achieve after dosing (CMax/Peak),half-life of the therapeutic plasma protein (FVIII half-life), and atime to a minimum (or lower) pre-specified threshold of theconcentration of the therapeutic plasma protein within the patient. Itshould be appreciated that in other embodiments, the user interface 700can include fewer fields or additional fields for the pharmacokineticprofile including V1 and V2 and/or assay type.

In some instances, the example tool 110 may provide a warning and/oralert if any of the pharmacokinetic profile data is outside of a certainpercentage of a sampled patient population used for creating thepharmacokinetic model 106. For instance, the tool 100 may indicate thatthe adjusted clearance value is outside of 95% of clearance values ofsampled patients within the same population set as the patientundergoing treatment. The warning and/or alert may be used as a triggerby a user to verify entered patient information. The warning and/oralert may also be used as an indication that the dosing regimen isabnormal or outside of dosing regimens for sampled patients with similarcharacteristics as the patient undergoing treatment.

In addition to providing the pharmacokinetic profile data shown in FIG.8, the example tool 110 also provides a graphical representation of theestimated pharmacokinetic profile and a dosing recommendation. FIGS. 9and 10 include diagrams of user interfaces 900 and 1000 that displaydosing and pharmacokinetic information (e.g., time-varying therapeuticplasma protein level in the patient (e.g., CL)) for a specific patient.The therapeutic plasma protein level is shown as a concentrationpercentage relative to a normal level of clotting factor VIII within apatient. However, in other embodiments, the therapeutic plasma proteinlevel may be shown as a unit of measure.

FIG. 9 includes a diagram of the user interface 900 that graphicallydisplays an estimated or approximate pharmacokinetic profile of apatient 902. The example pharmacokinetic profile 902 shows how atherapeutic plasma protein is metabolized in a patient over timestarting at a time when the therapeutic plasma protein is administered.The pharmacokinetic profile of the patient 902 is denoted by the solidline. The example user interface 900 also includes a comparison of thepharmacokinetic profile of the patient 902 to a pharmacokinetic profileof sample patients 904 used to create the pharmacokinetic model 106,which is denoted by the dashed line. The user interface 900 alsoincludes a shaded band 906 that represents ±20% of the pharmacokineticprofile of sample patients 904.

Moreover, the example user interface 900 includes a graphicalrepresentation of patient samples 908 and 910 in instances where thepatient received one or more blood tests after an infusion of thetherapeutic plasma protein. Patient sample 908 corresponds to a samplenot selected to be included within the determination of thepharmacokinetic profile of a patient 902 and patient samples 910correspond to selected samples for inclusion in the determination of thepharmacokinetic profile of a patient 902. The blood tests are performedto determine an amount of therapeutic plasma protein in the patientafter an initial infusion and may be performed to further refine thepharmacokinetic profile of a patient 902. For instance, instead ofperforming five or more blood draws after an infusion, the example PKserver 108 and/or tool 110 may be used to create the pharmacokineticprofile of a patient 902 using the data from fewer blood draws inconjunction with the pharmacokinetic profile of sample patients 904based on the pharmacokinetic model 106.

The example user interface 1000 of FIG. 10 enables a user to graphicallyview dosing changes based upon changes to dosing interval and/or aminimum (lower) specified threshold of the concentration of thetherapeutic plasma protein (e.g., target trough) based on thepharmacokinetic profile of a patient 902 shown in FIG. 9. For instance,FIG. 10 shows a graph of a dosing regimen that visually indicates how anadministered therapeutic plasma protein is metabolized based upon thepatient's estimated pharmacokinetic profile 902. The dosing regimenincludes a dosing interval of 72 hours such that the concentration ofthe therapeutic plasma protein does not fall below a target trough of30%. The example drug dosing tool 110 uses this information to calculatean estimated dosage (e.g., 48.0 IU or 0.76 IU/kg) that is to beadministered every 72 hours. The example tool 110 also calculates anamount of time that the therapeutic plasma protein level exceeds (e.g.,is below) the target trough. In other instances, the tool 110 mayprovide an indication of time that the therapeutic plasma protein levelis below the target trough, which corresponds to an amount of time thata patient is unprotected by the therapeutic plasma protein andsusceptible to bleeds.

The example tool 110 is configured to enable a user to adjust theinterval and target trough via the interface 1000 and accordingly changethe dosing regimen including the dosage and therapeutic plasma proteinlevel over time. It should be appreciated that changing either theinterval or the target trough does not change the estimatedpharmacokinetic profile of the patient 902. Instead, the example tool110 applies the selected interval or target trough to the determinedpharmacokinetic profile of the patient 902.

The interface 1000 configuration of example tool 100 enables ahealthcare provider to determine how dosing changes based upon changesto the interval or target trough. For instance, a healthcare providercan compare dosing regimens for an every-two-day dosing interval and anevery-three-day dosing interval (or additional intervals such as anevery-day dosing interval) to determine whether a dosing interval can beextended (or reduced) for a patient, thereby requiring fewer visits to ahealthcare facility and/or fewer self-treatments. The target troughenables the healthcare provider to determine how a dosing regimen isaffected by a desired minimum therapeutic plasma protein level in thepatient. For instance, a healthcare provider may determine that a 10%target trough is acceptable for a (relatively active) patient andaccordingly sets the target trough on the user interface 1000 to 10%.Responsive to receiving the selection of the target trough, the exampletool 110 determines an estimated dosage such that the concentration ofclotting factor VIII does not fall below the 10% threshold whilemaintaining an every-three-day dosing interval. The healthcare provideraccordingly uses the tool 110 to determine whether an every-three-daydosing regimen is appropriate for a 10% target trough such that thedosage or CMax does not exceed a safety threshold.

The example drug dosing tool 110 also provides the graphical therapeuticplasma protein level over time and dosage based upon a schedule (e.g., aweek, month, year, etc.). For instance, a user can select the ‘Schedule’button in the interface 1000, causing the tool 110 to display availabledays for dosing. A user selects which days a dosage is to be provided toa patient, causing tool 110 to determine a dosage and therapeutic plasmaprotein level over time such that the therapeutic plasma protein leveldoes not fall below the target trough. For example, FIG. 11 shows adiagram of an example user interface 1100 that enables a user to selectparticular days (and/or times) for providing a dosage of the therapeuticplasma protein. For example, a user may enter into the tool 110 that a1753 IU dosage of therapeutic plasma protein is to be provided to apatient on Monday, Wednesday, Friday, and Sunday using a 48 hour dosinginterval. A user may select anywhere on concentration line 1102 to viewthe date/time and specific concentration of clotting factor VIII withinthe patient.

FIG. 12 shows a diagram of a user interface 1200 that enables a user toview amounts of time where the amount of clotting factor VIII is above aspecified concentration and below a specified concentration. Forinstance, a user may select a ‘time below’ to be 3% and a ‘time above’to be 10%. In response to this information, the example tool 110 and/orthe PK server 108 determines an amount of time the amount of clottingfactor VIII is above 10% and below 3%. The example tool 110 alsographically displays this time within the graph of the user interface1200. This information shows, for example, an amount of time below 3%where a patient may be left unprotected and is susceptible to bleeds andan amount of time where the patient is fully protected.

The example drug dosing tool 110 also enables a user to store to thedatabase 116 (and/or a local memory of the client device 112) patientpharmacokinetic profiles in conjunction with dosing and therapeuticplasma protein level data. For instance, a user can select the ‘Save’button in interface 1000 of FIG. 10, causing the drug dosing tool 110 tosave to a data storage the information described in conjunction withFIGS. 5 to 12. The information may also be saved as a report. FIG. 13includes a diagram of a report 1300 of the saved information describedin conjunction with FIGS. 5 to 12. A healthcare provider may view report1300 to determine how a dosing regimen of therapeutic plasma protein wascalculated for a patient.

In addition to providing patient dosing information, the example tool110 may be configured in conjunction with the PK server 108 to transmitthe dosing information to a hospital information system and/or to aninfusion pump 120. For example, returning to FIG. 1, a healthcareprovider may use the tool 110 on client device 112 c to determine dosinginformation for a patient. The tool 110 may be configured to transmitthe dosing information to the PK server 108. The healthcare provider mayalso identify an infusion pump that will be providing the dosing.Responsive to receiving the dosing information, the PK server 108transmits the dosing information to an infusion pump and/or a hospitalinformation system. Alternatively, the PK server 108 may retain thedosing information until requested by an infusion pump. In instances inwhich a pump is not specified, the hospital information systemdetermines which pump is to provide the infusion to the patient andcauses the dosage information to be transmitted to the appropriate pump.

Alternatively, the example tool 110 on the client device 112 c maycommunicate the dosage information directly to the infusion pump 120(e.g., via near field communication, Bluetooth®, etc.). For instance,the tool 110 may be configured to cause the client device 112 c toestablish a communication session or to locate a proximately locatedpump. Upon establishing communication with the pump 120, the tool 110transmits the dosing information to program the infusion pump.

Additionally or alternatively, the tool 110 may be used directly with apatient. For instance, the example tool 110 may be configured totransmit a schedule to a patient after a healthcare provider hasselected a dosing regimen. For example, the tool 110 may transmit adosing regimen or schedule to the client device 112 of a patient thatinstructs the patient how much therapeutic plasma protein to infuse andwhen to infuse. The dosing regimen or schedule indicates (and mayinclude reminders) the specific days (and/or times) of a week, month,year, etc. that the patient is to receive a dosage of the therapeuticplasma protein. Further, tool 110 may be available to a patient toenable the patient to view previous treatments and to compare how adosing regimen changes based upon a change in dosing interval.

Marketing Tool Embodiment

In the previous embodiment, a healthcare provider uses the example tool110 to determine a dosing regimen to administer a therapeutic plasmaprotein to a patient. In a second embodiment, the example tool 110 mayinstead be configured to provide a generalized dosing regimen (e.g., adosing regimen for a theoretical patient) to demonstrate to a healthcareprovider the capabilities of a therapeutic plasma protein as part of asales or marketing presentation. For example, a sales representative maydemonstrate how the therapeutic plasma protein ADVATE drug performsunder every-two-day and every-three-day dosing regimens. The exampletool 110 may also compare how a first brand of therapeutic plasmaprotein performs for a theoretical patient compared to a second brand oftherapeutic plasma protein.

FIGS. 14 to 18 display user interfaces provided by the drug dosing tool110 in this marketing tool embodiment. The user interfaces showtheoretical patient data that a sales representative may use todemonstrate to a healthcare provider how therapeutic plasma protein canbe prescribed based upon a pharmacokinetic profile of a theoreticalpatient taking into account the theoretical patient's body weight andhalf-life time. The half-life time is the time it takes for a drug toreach half its original concentration in a patient.

In particular, the example tool 110 enables a sales representative todemonstrate to a healthcare provider how therapeutic plasma proteinperforms when the dosing is performed every two days versus every threedays for a specified theoretical patient. It should be appreciated thatthe user interfaces shown in FIGS. 14 to 18 are only exampleembodiments. In other examples, the layout and/or functionality of theuser interfaces may change based upon requirements of salesrepresentatives.

FIG. 14 includes a diagram of user interface 1400 that is provided bythe drug dosing tool 110 on the client device 112 of FIG. 1. Theinterface 1400 is configured to prompt a user to provide a currentdosing regimen specified for an actual patient or a theoretical patient.In this illustrated embodiment, a theoretical patient is specified toweigh 60 kg and have a drug half-life of 12 hours. Further, a userspecifies a dosing regimen of 2300 IU every 48 hours. Moreover, a userselects a trough threshold (e.g., a minimum or lower threshold) to be 1%using scroll bar 1401. The trough is shown within the user interface1400 as line 1402.

In response to providing the patient and drug parameters, the drugdosing tool 110 uses a pharmacokinetic model (e.g., the pharmacokineticmodel 106 described above) to determine a pharmacokinetic profile of thetheoretical patient. The drug doing tool 110 uses this profile todetermine a dosing regimen (e.g., dosage and interval). The tool 110graphically displays the dosing regimen as a concentration oftherapeutic plasma protein within the theoretical patient over a timeperiod (shown as line 1404). For example, at time ‘0’, 2300 IU of thedrug is shown to be dispensed to the theoretical patient, resulting in a76.7% concentration of the therapeutic plasma protein in the patient.The concentration of the therapeutic plasma protein decreases over thenext 48 hours based upon the determined pharmacokinetic profile of thetheoretical patient.

FIG. 15 shows the user interface 1400 of FIG. 14 after a user hasselected the ‘2 days’ button. Selection of this button causes the tool110 to determine an every-two-day dosing regimen based upon thepharmacokinetic profile of the theoretical patient. This regimenincludes a dose (e.g., 600 IU) and a graphical display of thetherapeutic plasma protein concentration within the theoretical patientover the time period (shown as line 1406). The example tool 110determines a dose amount for the two day dosing interval such that theconcentration of the therapeutic plasma protein does not fall below thespecified 1% target trough.

The user interface 1400 of FIG. 15 also provides a comparison of thedosing regimen initially provided by a user and the dosing regimendetermined by the tool 110. In the illustrated example, tool 110graphically indicates that the user only has to prescribe 600 IU insteadof 2300 IU every 48 hours. In other words, the tool 110 indicates thatthe user had overestimated the dosage required such that theconcentration of the therapeutic plasma protein does not fall below the1% target trough.

FIG. 16 shows the user interface 1400 of FIG. 14 after a user hasselected the ‘3 days’ button. Selection of this button causes the tool110 to determine an every-three-day dosing regimen based upon thepharmacokinetic profile of the theoretical patient. This regimenincludes a dose (e.g., 2600 IU) and a graphically display of thetime-varying therapeutic plasma protein concentration within thetheoretical patient (shown as line 1408). The tool 110 determines theregimen so that the concentration does not fall below the specified 1%target trough.

The user interface 1400 of FIG. 16 also displays a comparison of thedosing regimen initially provided by a user and the dosing regimendetermined using tool 110. In the illustrated example, the tool 110graphically indicates that a healthcare provider has to prescribe 2600IU every 72 hours such that the concentration does not fall below 1%during any time between doses. A sales representative can use thisgraphical comparison to show a healthcare provider that a dosage onlyhas to be increased slightly from a current dosage provided every 48hours to achieve the same protection from bleeds while increasing theamount of time between doses. It should be appreciated that theextension of the dosing interval places less stress on the patient(e.g., less trips to the healthcare provider) and on the healthcareprovider (e.g., fewer doses to administer).

A sales representative uses the graphs displayed in FIGS. 15 and 16 tographically illustrate to a healthcare provider how a dosing regimenchanges for the same theoretical patient using an every-two-day dosinginterval and an every-three-day dosing interval. The salesrepresentative can also use the tool to graphically highlight thebenefits of using an every-three-day interval by showing that thetherapeutic plasma protein can be administered to a patient every threedays without violating the 1% threshold. The sales representative maydisplay concurrently the every-three-day interval and the every-two-dayinterval by selecting the ‘Both’ button included within the userinterface 1400.

In addition to providing graphical displays of differences between theevery-two-day and every-three-day dosing regimens, the example drugdosing tool 110 also graphically shows how long a theoretical patient isleft unprotected based upon specified parameters. For example, the userinterface 1400 of FIG. 17 shows an indication 1410 displayed by the tool110 responsive to determining that the time-varying therapeutic plasmaprotein concentration within the theoretical patient (e.g., the line1404) falls below the target trough line 1402. In this embodiment, auser raises the scroll bar 1401 such that the target trough is increasedto 13%. The example tool 110 determines a duration of time that thetherapeutic plasma protein concentration is below 13% and shows thisduration at indication 1410. The example tool 110 may also determine anew dosing regimen (e.g., an interval and/or dose) so that thetherapeutic plasma protein concentration does not fall below the 13%target trough.

FIG. 18 includes a diagram of user interface 1800 that displays anindication 1802 as to how long a theoretical patient was leftunprotected by a therapeutic plasma protein. Indication 1802 is basedupon the duration of time that the therapeutic plasma proteinconcentration resides below the 13% target trough, as determined inconjunction with FIG. 17. The example tool 110 also predicts a number ofbleeds a year based upon the duration of time that the therapeuticplasma protein concentration resides below the target trough. In theillustrated example, the indication 1802 includes a graph showing that atheoretical patient would be left unprotected for 39 hours a week, whichcould result in 2.3 bleeds a year. A sales representative can use theinformation presented in FIGS. 17 and 18 to show healthcare providershow an every-three-day dosing regimen reduces (or eliminates) times atwhich a patient is unprotected from the benefits of the therapeuticplasma protein.

Flowchart of Example Drug Dosing Tool Usage Embodiment

FIGS. 19 and 20 show a flow diagram illustrating example procedure 1900to determine a dosing regimen for a patient (or theoretical patient),according to an example embodiment of the present disclosure. Theexample procedure 1900 may be carried out by, for example, the PK server108 and/or drug dosing tool 110 described in conjunction with FIGS. 1 to18. Although the procedure 1900 is described with reference to the flowdiagram illustrated in FIGS. 19 and 20, it should be appreciated thatmany other methods of performing the functions associated with theprocedure 1900 may be used. For example, the order of many of the blocksmay be changed, certain blocks may be combined with other blocks, andmany of the blocks described are optional.

Procedure 1900 begins when drug dosing tool 110 receives an indicationthat a user (e.g., a healthcare provider, sales representative, patient,etc.) desires to determine a dosing regimen (block 1902). The indicationcan coincide with operating the drug dosing tool 110 on a client device112 and/or accessing the drug dosing tool on the PK server 108.Responsive to receiving the request for the dosing regimen, the drugdosing tool provides a prompt for patient information (e.g., bodyweight, gender, age, activity level, etc.) (block 1904). The patientinformation can correspond to an actual or theoretical patient.

The example drug dosing tool 110 also provides a prompt for previoustherapeutic plasma protein treatments for the patient (block 1908). Insome embodiments, the drug dosing tool 110 may access the previoustreatment information from a stored data structure (e.g., the database116). The example drug dosing tool 110 accesses and refines apharmacokinetic model (e.g., the pharmacokinetic model 106) based uponthe previous treatments and/or samples (block 1910). It should beappreciated that previous treatment information may not be available orprovided to the drug dosing tool 110. In these embodiments, drug dosingtool 110 uses the pharmacokinetic model 106 without modification. Itshould also be appreciated that in this procedure 1900 thepharmacokinetic model 106 has already been created and provided to thePK server 108 and/or the tool 110. In other examples, thepharmacokinetic model 106 may be created from patient from the samples104 anytime during and/or before the steps specified in blocks 1902 to1910).

The example drug dosing tool 110 uses the (refined or modified)pharmacokinetic model and the patient information to determine a(estimated or approximate) pharmacokinetic profile for the patient(block 1912). The drug dosing tool 110 then provides a prompt for adosing interval and/or a target trough (block 1914). In some instances,the dosing tool 110 may use a default target trough (e.g., 1%) when atrough is not provided or specified by a user. The drug dosing tool 110next determines a dose of therapeutic plasma protein and an estimationof a concentration of the therapeutic plasma protein in the patient overa specified time period (block 1916). The drug dosing tool 110graphically provides to the user a dosing regimen including thedetermined dosing and concentration over time (block 1918).

After providing the dosing regimen, the drug dosing tool 110 in theillustrated embodiment determines if the user has selected a differentdosing interval (block 1920). For instance, a user could select to viewan every-two-day and an every-three-day dosing interval. If the userprovides a different interval, the example drug dosing tool 110 returnsto block 1916 and determines a new dosing regimen based upon theselected interval.

However, if the user does not select a different interval, the exampledrug dosing tool 110 determines whether the user selected a differenttarget trough (block 1922). If the user selects a different trough, theexample drug dosing tool 110 determines a duration of time in which thetherapeutic plasma protein concentration is less than the trough level(block 1924). The drug dosing tool 110 then provides to the user agraphical indication of this duration (block 1926). The drug dosing tool110 next determines if the user selects for the dosing tool 110 todetermine a dosing regimen based upon the newly provided target trough(block 1928). If the user desires a dosing regimen based upon the newtrough, the example procedure 1900 returns to block 1916 and the drugdosing tool 110 determines a new regimen.

However, if a user does not desire to view a new dosing regimen, theexample drug dosing tool 110 provides a prompt to store the currentdosing regimen (block 1930). Responsive to storing the dosing regimen,the example procedure 1900 ends. Alternatively, (e.g., as selected bythe user) the example procedure 1900 returns to block 1902 to determinea dosing regimen for another patient and/or a dosing regimen for thesame patient for another visit to the healthcare provider.

Patient Activity Level Example Embodiment

FIGS. 21 and 22 are diagrams that show an example embodiment where apharmacokinetic profile for a specific patient is adjusted based onactivity level. FIG. 21 shows a data structure 2100 that includes anormal dosing regimen in a first column (i.e., Prophylaxis (IU)), anactivity level for a patient in a second column, and an adjustment tothe dosing regimen in a third column. Each row in the data structure2100 corresponds to a day of a week.

An estimated or approximate pharmacokinetic profile and thecorresponding normal dosing regimen is determined for a specific patient(e.g., Hem A) using the procedures discussed above in conjunction withFIGS. 3 to 13. In this embodiment, the example PK server 108 of FIG. 1is configured to adjust the normal dosing regimen based on activities ofa patient. This adjustment compensates for increases in risk forbleeding as a result of an increased activity level, which increases theneed to maintain the therapeutic plasma protein level in the patientabove a higher threshold. As discussed above, the amount orconcentration of therapeutic plasma protein within a patient isdependent on the patient's metabolism.

To compensate for these temporary increases in risk, the example PKserver 108 may prompt a patient or healthcare provider for a weeklyschedule of activities. In other instances, the PK server 108 mayreceive a schedule via an electronic calendar or activity log managed bya patient. In this embodiment, the activities are classified byintensity such that with lower intensity activities separated fromactivities with relatively greater intensities. The intensity may alsobe based on a duration of the activity. The PK server 108 may include adata structure that relates different activities with a correspondingintensity level (with adjustments made for duration).

The example PK server 108 uses the activities and associated intensitiesto adjust the normal pharmacokinetic profile of the patient to determinea modified pharmacokinetic profile based on temporary periods ofincreased bleeding risk. The PK server 108 then compares the modifiedpharmacokinetic profile to determine if there is a time period in whichthe calculated therapeutic plasma protein concentration falls below atarget trough. If a time period is determined in which the concentrationfalls below the target trough, the PK server 108 determines when and howmuch of an extra dosage of therapeutic plasma protein is to be providedto the patient. In other instances, the PK server 108 and/or the tool110 may use a pharmacokinetic model 106 that includes sample patientswith similar active lifestyles as the patient under care.

In the example of FIGS. 21 and 22, the PK server 108 determines that anactivity planned for Monday (e.g., Mountain Biking) is relativelyintense, which increases the need to keep the concentration of thetherapeutic plasma protein above a target trough level (e.g., 3%). ThePK server 108 accordingly determines that an extra dosage of 1000 IU isto be administered to the patient on Monday so that the concentration ofthe therapeutic plasma protein does not fall below 3%.

FIG. 22 shows a graph 2200 of the modified pharmacokinetic profile basedon temporary changes in activity related bleed risk. The graph 2200shows that before the first Tuesday (before the extra dosage isapplied), the concentration of therapeutic plasma protein in the patientfalls below 3%. The graph 2200 also shows that before the secondTuesday, 1000 IU is provided to the patient on Monday. This extra dosagecauses the concentration of therapeutic plasma protein to remain abovethe 3% target trough. In this manner, the example PK server 108 reducesthe chances of a bleed for relatively active patients.

Therapeutic plasma protein Comparison Embodiment

The example model generator 102, the PK server 108, and the drug dosingtool 110 were described in conjunction with determining a dosing regimenfor one particular type of therapeutic plasma protein. However, in someexamples, the model generator 102 may generate pharmacokinetic modelsfor multiple types or brands of therapeutic plasma protein. Thisenables, for example, a user (e.g., a sales representative) to comparehow the concentrations of the different therapeutic plasma proteinsdiffer for the same patient for the same or different dosing intervals.

For example, a user may provide to the tool 110 patient information. Thepatient information is incorporated by the tool 110 into a firstpharmacokinetic model for a first brand of therapeutic plasma proteinand a second pharmacokinetic model for a second brand of therapeuticplasma protein. The user may then enter into the tool 110 a prescribeddosing regimen for the first therapeutic plasma protein and a prescribeddosing regimen for the second therapeutic plasma protein, which causesthe tool 110 to display concurrently within a user interface aconcentration of the first therapeutic plasma protein and the secondtherapeutic plasma protein over a time period for the patient. Theexample tool 110 may also enable the dosing intervals and/or doses to bemodified (to the extent allowed or recommended by the manufacturertherapeutic plasma protein) to show how changes affect theconcentration.

In particular, a user may use the tool 110 to show that the first brandof therapeutic plasma protein may be provided at three day dosingintervals with a dosage of 2600 IU while remaining above a target troughof 3% between doses. In comparison, the tool 110 shows the second brandof therapeutic plasma protein has to be provided every two days with adosage of 2000 IU to remain above the same 3% target trough. In thisinstance, the first brand of the therapeutic plasma protein may be thebetter alternative to administer to a patient to reduce the number ofinfusions required per week while keeping the patient safe from bleeds.

Treatment Embodiment

As discussed above, the example drug dosing tool 110 and/or the PKserver 108 determines an amount of therapeutic plasma protein (e.g.,clotting factor VIII) to administer to a patient. To administer thetherapeutic plasma protein to a patient, in one aspect, the therapeuticplasma protein includes one or more pharmaceutically acceptablecarriers. The phrases “pharmaceutically” or “pharmacologically”acceptable refer to molecular entities and compositions that are stable,inhibit protein degradation such as aggregation and cleavage products,and in addition, do not produce allergic, or other adverse reactionswhen administered using routes well-known in the art. “Pharmaceuticallyacceptable carriers” include any and all clinically useful solvents,dispersion media, coatings, antibacterial and antifungal agents,isotonic and absorption delaying agents and the like.

The pharmaceutical formulations are administered orally, topically,transdermally, parenterally, by inhalation spray, vaginally, rectally,or by intracranial injection. The term parenteral as used hereinincludes subcutaneous injections, intravenous, intramuscular,intracisternal injection, or infusion techniques. Administration byintravenous, intradermal, intramusclar, intramammary, intraperitoneal,intrathecal, retrobulbar, intrapulmonary injection and or surgicalimplantation at a particular site is contemplated as well. Generally,compositions are essentially free of pyrogens, as well as otherimpurities that could be harmful to the recipient.

Single or multiple administrations of the therapeutic plasma protein arecarried out with the dose levels and pattern being selected by ahealthcare provider. As discussed, the dosage regimen for thetherapeutic plasma protein is based on various characteristics of thepatient including age, gender, body weight, condition, activity level,diet, etc. The dosing regimen may also be based on a type of disease tobe treated, the severity and course of the disease, whether thetherapeutic plasma protein is administered for preventive or therapeuticpurposes, previous therapy, a patient's clinical history and response tothe therapeutic plasma protein, and the discretion of the healthcareprovider. By way of example, a typical dose of a recombinant clottingfactor FVIII therapeutic plasma protein is approximately 30 IU/kg to 50IU/kg.

In one embodiment, a clotting factor FVIII therapeutic plasma proteinmay be administered by an initial bolus followed by a continuousinfusion to maintain therapeutic circulating levels of the therapeuticplasma protein. In another embodiment, the inventive compound may beadministered as a one-time dose. Those of ordinary skill in the art willreadily optimize effective dosages and administration regimens asdetermined by good Tpractice and the clinical condition of theindividual patient in conjunction with the results provided by theexample tool 110. The frequency of dosing may depend on thepharmacokinetic parameters of the agents and the route ofadministration. The final dosage regimen is determined by the healthcareprovider, considering various factors which modify the action of drugs,e.g. the drug's specific activity, the severity of the damage and theresponsiveness of the patient, the age, condition, body weight, gender,and diet of the patient, the severity of any infection, time ofadministration and other clinical factors.

Preferably, an effective dose of the therapeutic plasma protein is 15-85IU/kg (15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30,31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48,49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 62, 64, 65, 66,67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84,or 85 IU/kg) and the dosing interval is once every 1-5, 2-5, 3-5, 3-6,3, 4, 5, 6, 7, or 8 or more days, or three times per week, or no morethan three times per week. Additional therapeutic doses that may be usedare about 10 to about 150 IU/kg, more specifically, about 100-110,110-120, 120-130, 130-140, 140-150 IU/kg, and more specifically, about110, 115, 120, 125, 130, 135, 140, 145, or 150 IU/kg. The dose should behigh enough to experience efficacy, but not too high to avoid severeadverse effects. This therapeutic window is different for each patient,given environmental and genetic factors.

The relationship between patient and treatment-related variablesincluding average Cmax, time below a target trough, and time spent abovea specified threshold, for example, 5, 10, 20, 30% and 40% of aconcentration of the therapeutic plasma protein within a patient, andrisk for bleeding on prophylaxis are indices that may be used tooptimize a dosing regimen. In this manner, individualized regimens withhemostatically-effective, non-hemophilic FVIII ranges and with increasedprophylactic efficacy are created and implemented. In variousembodiments, annual bleeding rates (“ABR”) decrease by at least 50, 60,70, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96,97, 98 or 99% when, for example, a PK-guided dosing regimen as describedabove is followed as compared to on-demand dosing regimen.

Increasing time with a therapeutic plasma protein concentration below 1IU dL(−1) is associated with increased total hemorrhages andhemarthroses in severe hemophilia A patients treated with regularprophylaxis regimens. Targeting trough levels at ≥1% above baselineusing PK-guided dosing at 72 h intervals has been demonstrated to be aneffective treatment strategy. While targeting FVIII trough at >1% abovebaseline is generally effective, this strategy alone may not be suitablefor all patients, especially those with a recent history of high ABRs onon-demand therapy. Such patients may require alternative dosing regimensincluding higher doses and/or shorter dose intervals to achieve highertroughs and/or more frequent peaks of therapeutic plasma proteinconcentration.

In one embodiment, patients using a PK-guided dosing regimen experienceda median ABR of 2.0 (range 0-17.1) representing a 96% reduction in ABRfrom on-demand therapy. The individual FVIII therapeutic plasma proteinhalf-lives (median: 11.7 hr; range: 7.3-30.7; IQR: 10.1-13.6; 5-95%percentiles: 7.7-21.4), and therefore, the FVIII therapeutic plasmaprotein dose/infusion (median 41.3 (IU/kg), range 18.9-84.9) variedwidely in the study cohort. This enabled examination of the role oftreatment- and patient-related variables other than FVIII therapeuticplasma protein troughs in achieving low ABRs in patients usingindividualized regimens.

Data from patients prescribed PK-guided dosing given every third day(n=34) were examined. Average Cmax for these patients was estimatedusing individual IVR values for each patient and their average dose perprophylactic infusion. The concentration of the therapeutic plasmaprotein and time spent above 5, 10, 20, 30, or 40% therapeutic plasmaprotein FVIII levels (i.e., within hemostatically effective,non-hemophilic range) in each patient were extrapolated using parametersfrom individual PK profiles and actual infusion records. A negativebinomial multivariate regression model was used for analysis with ageand BMI as covariates.

The estimate for average Cmax ranged from 24.3 to 167.5% (median 70.9%)in patients on PK-guided dosing with an every-three-day infusionschedule. As shown in graph 2300 of FIG. 23, a significant relationshipbetween lower Cmax and increased risk for bleeding was seen. FIG. 24includes a table 2400 that provides average Cmax and risk for bleeding.Time spent above a 20% concentration of the therapeutic plasma proteinFVIII (joint bleeding only), time spent above a 30% concentration of thetherapeutic plasma protein FVIII, and time spent above a 40%concentration of the therapeutic plasma protein showed a significantrelationship with lower ABR. FIG. 25 shows a graph 2500 of a percent oftotal time spent above a 30% concentration of the therapeutic plasmaprotein FVIII in relation to bleeding risk. FIG. 26 shows a table 2600of time spent in a non-hemophilic range in relation to a bleeding risk.

Similar significant relationships were found in all therapeutic plasmaprotein concentration variables tested (e.g., above 5%, 10%, and 20%).However, the co-efficient variable decreased with increasing averagetherapeutic plasma protein concentrations over the course of a week.FIG. 27 includes a diagram of a graph 2700 of average therapeutic plasmaprotein concentrations over the course of a week (“AUC”) in relation tothe bleed rate over the course of a year. FIG. 28 includes a table 2800that shows average therapeutic plasma protein concentrations over thecourse of a week in relation to a risk for patient bleeding. As shown inFIG. 29, average Cmax, Time above % and weekly AUC variables were allstrongly correlated.

A substantial reduction in ABR during prophylaxis was seen in eachpatient. However many patients with higher ABR on prophylaxis appearedto have had more bleeding episodes during the preceding on-demand periodand had a lower % ABR reduction on prophylaxis, as shown in graph 3000of FIG. 30. These results demonstrate a relationship between higher Cmaxvalues and/or time spent within “hemostatically effective”,non-hemophilic FVIII range and better prophylactic efficacy in patientson PK-guided dosing given every third day. Conversely, increasing timespent within the lower FVIII therapeutic plasma protein range increasedrisk for bleeding. While targeting FVIII therapeutic plasma proteintrough at >1% above baseline is generally effective and widely acceptedin the scientific community, this strategy alone may not be suitable forall patients, especially those with a recent history of high ABRs onon-demand therapy. Such patients may require alternative dosing regimensincluding higher doses and/or shorter dose intervals to achieve highertroughs and/or more frequent peaks.

Processor

A detailed block diagram of electrical systems of an example computingdevice (e.g., the model generator 102, PK server 108, and/or the clientdevice 112) is illustrated in FIG. 31. In this example, the devices 102,108, and/or 112 include a main unit 3102, which preferably includes oneor more processors 3104 communicatively coupled by an address/data bus3106 to one or more memory devices 3108, other computer circuitry 3110,and one or more interface circuits 3112. The processor 3104 may be anysuitable processor, such as a microprocessor from the INTEL PENTIUM® orCORE™ family of microprocessors. The memory 3108 preferably includesvolatile memory and non-volatile memory. Preferably, the memory 3108stores a software program that interacts with the other devices in theenvironment 100, as described above. This program may be executed by theprocessor 3104 in any suitable manner. In an example embodiment, memory3108 may be part of a “cloud” such that cloud computing may be utilizedby devices 102, 108, and/or 112. The memory 3108 may also store digitaldata indicative of documents, files, programs, webpages, patientsamples, pharmacokinetic models, patient pharmacokinetic profiles, etc.retrieved from (or loaded via) devices 102, 108, and/or 112.

The example memory devices 3108 store software instructions 3123,patient samples/ pharmacokinetic models 3124, application interfaces3126, user interface features, permissions, protocols, identificationcodes, content information, registration information, event information,and/or configurations. The memory devices 3108 also may store network orsystem interface features, permissions, protocols, configuration, and/orpreference information 3128 for use by the devices 102, 108, and/or 112.It will be appreciated that many other data fields and records may bestored in the memory device 3108 to facilitate implementation of themethods and apparatus disclosed herein. In addition, it will beappreciated that any type of suitable data structure (e.g., a flat filedata structure, a relational database, a tree data structure, etc.) maybe used to facilitate implementation of the methods and apparatusdisclosed herein.

The interface circuit 3112 may be implemented using any suitableinterface standard, such as an Ethernet interface and/or a UniversalSerial Bus (USB) interface. One or more input devices 3114 may beconnected to the interface circuit 3112 for entering data and commandsinto the main unit 3102. For example, the input device 3114 may be akeyboard, mouse, touch screen, track pad, track ball, isopoint, imagesensor, character recognition, barcode scanner, microphone, and/or aspeech or voice recognition system.

One or more displays, printers, speakers, and/or other output devices3116 may also be connected to the main unit 3102 via the interfacecircuit 3112. The display may be a cathode ray tube (CRTs), a liquidcrystal display (LCD), or any other type of display. The displaygenerates visual displays generated during operation of the device 102,108, and/or 112. For example, the display may provide a user interfaceand may display one or more webpages received from the device 102, 108,and/or 112. A user interface may include prompts for human input from auser of the devices 102, 108, and/or 112 including links, buttons, tabs,checkboxes, thumbnails, text fields, drop down boxes, etc., and mayprovide various outputs in response to the user inputs, such as text,still images, videos, audio, and animations.

One or more storage devices 3118 may also be connected to the main unit3102 via the interface circuit 3112. For example, a hard drive, CDdrive, DVD drive, and/or other storage devices may be connected to themain unit 3102. The storage devices 3118 may store any type of data,such as identifiers, identification codes, registration information,patient samples, patient information, pharmacokinetic models, patientpharmacokinetic profiles, treatment regimens, statistical data, securitydata, etc., which may be used by the devices 102, 108, and/or 112.

The computing device 102, 108, and/or 112 may also exchange data withother network devices 3120 via a connection to a network 3121 (e.g., theInternet) or a wireless transceiver 3122 connected to the network 3121.Network devices 3120 may include one or more servers, which may be usedto store certain types of data, and particularly large volumes of datawhich may be stored in one or more data repository. A server may processor manage any kind of data including databases, programs, files,libraries, identifiers, identification codes, registration information,content information, patient samples, patient information, treatmenthistory related to clotting factor VIII, pharmacokinetic models, patientpharmacokinetic profiles, treatment regimens, statistical data, securitydata, etc. A server may store and operate various applications relatingto receiving, transmitting, processing, and storing the large volumes ofdata. It should be appreciated that various configurations of one ormore servers may be used to support, maintain, or implement the devices102, 108, and/or 112 of the environment 100. For example, servers may beoperated by various different entities, including operators of the PKserver 108, hospital systems, patients, drug manufacturers, serviceproviders, etc. Also, certain data may be stored in one of the devices102, 108, and/or 112 which is also stored on a server, eithertemporarily or permanently, for example in memory 3108 or storage device3118. The network connection may be any type of network connection, suchas an Ethernet connection, digital subscriber line (DSL), telephoneline, coaxial cable, wireless connection, etc.

Access to the devices 102, 108, and/or 112 can be controlled byappropriate security software or security measures. An individualthird-party client or consumer's access can be defined by the device102, 108, and/or 112 and limited to certain data and/or actions.Accordingly, users of the environment 100 may be required to registerwith one or more computing devices 102, 108, and/or 112.

Additional Patient Model Generation Embodiment

As discussed above in connection with FIGS. 1 and 2, the example modelgenerator 102 is configured to determine or approximate apharmacokinetic profile of a patient using a Bayesian model (e.g., themodel described in Sheiner et al. Journal of Pharmaceutical Sciences1982) of pharmacokinetic profiles (PK) of sampled patients (i.e., theBjörkman population pharmacokinetic (PK) model developed from clinicaltrial data involving 152 study subjects ranging in age from 1 to 66years old). The use of the Bayesian model enables fewer patient bloodsamples to be drawn to determine a pharmacokinetic profile of a patient.For instance, the Society of Thrombosis and Haemostasis (“ISTH”)recommends that ten blood samples be collected from a patient over a 48hour post-infusion of clotting factor VIII time period. However, thecollection of ten samples over a 48 hour period is impractical andoverly burdensome on patients and clinicians.

The example model generator 102 is configured to use as few as twopatient samples in connection with the Bayesian model to determine orapproximate a pharmacokinetic profile of a patient. Generally, the timesof the sample collection relate to how the von Willebrand factor (“vWF”)binds to clotting factor VIII during blood circulation. vWF is a bloodglycoprotein that binds to other proteins including clotting factor VIIIto help platelet adhesion (e.g., blood clotting) during bleeds. Unboundclotting factor VIII has a relatively short half-life of approximately 1to 1.5 hours. vWF bound to clotting factor VIII (i.e., a vWF/FVIIIcomplex) has a half-life of approximately 12 to 24 hours. Based on thisinformation, relatively accurate patient models may be determined when afirst sample is collected at approximately 1.5 to 4 hours after aninfusion of clotting factor VIII, which corresponds to the half-life ofunbound clotting factor VIII and a second sample is collected at 23 to36 hours after the infusion, which corresponds to the half-life of thevWF/FVIII complex. More specifically, the first sample is collected atapproximately 3 to 4 hours (+/−30 minutes) hours after an infusion ofclotting factor VIII and the second sample is collected at 24 to 32hours (+/−30 minutes) after the infusion.

Different patients have their own unique metabolism and disposition ofclotting factor VIII. The example model generator 102 of FIG. 1 isconfigured to compare the two samples collected from the patient to theBjörkman population model to determine patients with similar metabolismcharacteristics. The model generator 102 may select the population modelfrom a plurality of population models stored in a database based on thepatient's demographic profile (e.g., age, body weight, height, BMI,etc.). In this example, each population model can be associated with aparticular set of demographic characteristics of a group of individualssuch that the model generator 102 selects the population modelassociated with the demographic characteristics that match those of thepatient. In another example, the model generator 102 may dynamicallygenerate the population model by pulling stored patient sample dataassociated with those patient's having a similar demographic profile tothat of the patient. The model generator 102 is configured to use thesesimilarities in determining the pharmacokinetic profile of the patient(i.e., the demographic similarities between the patient and theindividuals represented in the Björkman population model). The examplemodel generator 102 is accordingly able to determine an optimal dosingregimen (e.g., dose and frequency) for different patients to maintain atherapeutically effective level of clotting factor VIII over a dosinginterval in virtually any patient.

As discussed above, the risk of bleeding appears to increasedramatically when clotting factor VIII reaches low levels betweeninfusions. Maintaining clotting factor VIII above 1 IU/dL, or highersignificantly reduces the chances of a blood in a patient. However, the1 IU/dL threshold varies from patient to patient and can be anywherebetween 1-10 IU/dL as the therapeutically effective threshold for dosingas often as every 1 to 3 days. Notably, the 1 IU/dL threshold of aparticular patient may significantly from those patients represented inthe population model having similar demographic profiles as theparticular patient. Specifically, those patients with shorter clottingfactor VIII half-lives may have a higher bleed risk and may accordinglybe dosed more frequently, and/or at higher dosing levels. For example,FIG. 32 shows a diagram of an amount of time in which clotting factorVIII was above a 1 IU/dL threshold for a sample of patients with longerhalf-lives. In comparison, FIG. 33 shows a diagram of an amount of timein which clotting factor VIII was above a 1 IU/dL threshold for patientswith shorter half-lives (i.e., half-lives less than 12 hours). Asillustrated in FIGS. 32 and 33, patients with longer half-lives have avery low risk of falling below the 1 IU/dL threshold while patients withshorter half-lives have comparably more risk of falling below the 1IU/dL threshold. An appropriate dose amount and frequency is accordinglyimportant in balancing convenience versus bleeding risk and should takeinto account a patient's clotting factor VIII half-life.

Examination has found that patients with a very low vWF, and hence ashorter half-life, often had PK parameters that were over-corrected bythe model generator 102 towards the population mean. The over-correctionwas attributed to not placing enough weight (e.g., relative importance)on the individual patient's observed clotting factor VIII activitylevel. The over-correction meant that some patients with low vWF wererecommended a lower dose than should have been prescribed, therebyexposing those patients to an increased risk of bleeding. However, vWFis not typically measured in routine clinical practice and therefore isnot included in the population models. To account for vWF withoutdirectly measuring for vWF, the example model generator 102 isconfigured to account for the contribution of vWF and itspharmacokinetics using a pre-fit stage or evaluation to determine ifmore weight (e.g., relative importance) should be given to a patient'stwo or more samples and less weight (e.g., relative importance) to thepopulation data. The use of the pre-fit stage or evaluation by the modelgenerator 102 provides more accurate pharmacokinetic profile for apatient, thereby enabling an appropriate dose and frequency to bedetermined.

The pre-fit stage or evaluation performed by the example model generator102 evaluates the disappearance, metabolism, or clearance of a patient'sclotting factor VIII over time. A patient with low vWF will have lessvWF/FVIII complex, leading to lower measured activity or metabolism.Increased clotting factor VIII clearance is associated with lower vWFlevels, with an approximately linear relationship, until vWFmeasurements are about 100 to 120 IU/dL. Afterwards, there is noapparent impact of vWF on clotting factor FVIII clearance.

An example pre-fitting uses a non-compartmental approach (NCA) to fitthe patient's sampled data. Specifically, it uses a log-linearregression of clotting factor VIII (FVIII) activity levels versus time.The activity levels versus time data can be for time points that aregreater than or equal to a predetermined amount of time (e.g., 2.5hours) after an infusion. The regression can be accomplished using anordinary least square (OLS) regression. In other words, the modelgenerator 102 generates a linear regression model with an interceptcorresponding to a logarithmic function of the FVIII activity levelsagainst an actual time point for patient samples. The time pointscorrespond to those patient samples available after, e.g., 2.5 hoursfrom an infusion (e.g., a PK infusion). The model generator 102calculates an empirical estimate, λ_(z), of the patient's FVIIIelimination rate constant by obtaining an absolute value of a slope ofthe log-linear regression.

Additionally, the model generator 102 fits the patient sample data usingthe population Björkman model using a Bayes objective function. Themodel generator 102 denotes, as β, an estimated first-order rateconstant for the FVIII elimination process (e.g., a populationelimination rate constant of FVIII) defined by the fitting of thepatient sample data to the population Björkman model.

The model generator then determines a relationship between the empiricalestimate, λ_(z), and the population elimination rate constant, β. In oneaspect, the relationship is calculated at the ratio of the empiricalestimate, λ_(z), relative to the population elimination rate constant, β(e.g., relationship==“λ_(z)/β”). If the ratio is less than or equal to1, the model generator 102 determines that sufficient weight (e.g.,adequate relative importance) is being applied to the patient's sampleddata relative to the population model. As such, the model generator 102generates a PK profile of the patient using the standard populationBjörkman model. If the ratio is greater than 1, the model generatordetermines that insufficient weight (e.g., too low of a relativeimportance) is being applied to the patient's sample data relative tothe population Björkman model. Accordingly, the model generator 102increases the weight applied to the patients sampled data relative tothe population Björkman model. This can occur by increasing a weightapplied to the patient's sampled data relative to the populationBjörkman model, decreasing a weight applied to the population Björkmanmodel relative to the patient's sampled data, or some combination of thetwo such that a relative weight applied to the patient sampled data isincreased from a current weighting. In one particular example, thepatient sampled data can be fit to the Björkman model via a Bayesobjective function using an extra multiplicative constant in the termfor clearance. This extra multiplicative constant can be the ratiodefined by “λ_(z)/β”.

Another example pre-fitting step uses a log-linear regression ofmeasured clotting factor VIII clearance or activity versus time, usingat least two well-selected samples, to yield an empirical estimate ofλ_(z). It should be noted that this λ_(z) serves as a preliminaryestimate and may only potentially be used by the model generator 102 toupdate the Bayesian model prior to generating the pharmacokineticprofile of the patient.

After the pre-fitting step, the example model generator 102 isconfigured to use the Bayesian algorithm or model to determine patientparameter estimates, as discussed above in connection with equations (1)to (4). The model generator 102 is configured to compare the empiricalestimate of λ_(z) from the individual patient to the Bayesian estimateof the elimination rate constant. If a ratio of the comparison is lessthan or equal to 1, the model generator 102 concludes the analysis byreporting the Bayesian fit estimates and determining the pharmacokineticprofile of the patient. However, if the ratio is greater than 1, themodel generator 102 is configured to use the empirical estimate of λ_(z)to temporarily update the Bayesian model and refit the patient's sampledata to the population data.

FIG. 34 shows a diagram of clotting factor FVIII clearance for 27different patients over time. It should be appreciated that pre-dose vWFlevels were available for this data set. To estimate λ_(z) (i.e.,terminal or elimination phase rate constant) for each patient, theexample model generator 102 is configured to determine a slope of theclotting factor FVIII clearance line at a terminal or elimination phase,which is typically after 24 hours. The slope of the line after terminalphase of clotting factor FVIII activity level corresponds to a rateconstant. The model generator 102 then compares this empirical estimateof the rate constant to the Bayesian estimate of the elimination rateconstant to determine if a ratio of the empirical estimate to theBayesian estimate of the elimination rate constant is greater than orequal to 1. The model generator 102 is configured to use the empiricalestimate of λ_(z) to temporarily update the Bayesian model and refit thepatient's sample data to the population data if the ratio is greaterthan 1. If not, the model generator 102 performs a Bayesian fir analysisto determine the pharmacokinetic profile of the patient.

Additionally or alternatively, the model generator 102 may use thepatient sample data to determine a half-life for the patient. Patientswith a half-life greater than 12 hours are not typically over-corrected.For these patients, the model generator 102 is configured to weight thepopulation data more heavily than the patient's sample data. However,patients with a half-life less than 12 hours are typicallyover-corrected to the population mean. For these higher-risk patients,the model generator 102 is configured to weight the patient sample datamore heavily than the population data. The weighting of patient sampledata can be accomplished by using a variable (e.g., a weighting factor)that is assigned a numerical value. The numerical value enables themodel generator 102 to determine a relative importance of the patient'ssample data to that of the population data. As such, an absolute valueof the numerical value can determine a level of weighting of thepatient's sample data relative to the population data.

FIG. 35 shows a diagram of an amount of time in which clotting factorVIII was above a 1 IU/dL threshold for patients in which the pre-fittingstep was used by the model generator 102. As illustrated in FIG. 35, theuse of the pre-fitting step results in at least 90% or more of thepatients to have at least 80% of their dosing intervals above the 1IU/dL threshold regardless of the patient's clotting factor FVIIIhalf-life. The use of the pre-fitting step accordingly accounts for anyover-correction for patients with low levels of vWF.

It should be appreciated that in other embodiments, the vWF levels maybe measured by performing a blood draw prior to administering clottingfactor FVIII. Further, activity of vFW and clotting factor FVIII may bedetermined from blood samples drawn after the infusion. Together, thesemeasurements may provide a vWF clearance over time, which may be used bythe model generator 102 to update and/or refine the Bayesian modeland/or refine the pharmacokinetic profile of a patient. For example, theBayesian model may account for vWF as a covariate related to theclearance of clotting factor FVIII to provide guidance for FVIII dosageamount, for a given dosing frequency and target maintenance activitythreshold.

It will be appreciated that all of the disclosed methods and proceduresdescribed herein can be implemented using one or more computer programsor components. These components may be provided as a series of computerinstructions on any conventional computer-readable medium, includingRAM, ROM, flash memory, magnetic or optical disks, optical memory, orother storage media. The instructions may be configured to be executedby a processor, which when executing the series of computer instructionsperforms or facilitates the performance of all or part of the disclosedmethods and procedures.

It should be understood that various changes and modifications to theexample embodiments described herein will be apparent to those skilledin the art. Such changes and modifications can be made without departingfrom the spirit and scope of the present subject matter and withoutdiminishing its intended advantages. It is therefore intended that suchchanges and modifications be covered by the appended claims.

What is claimed is:
 1. A method for providing a clotting factor VIIIdosing regimen comprising: collecting two blood samples from a patientafter an infusion of clotting factor VIII; determining a clotting factorVIII clearance for the patient based on the two blood samples;determining if a patient has a half-life greater than a predeterminedthreshold; determining, via a processor, an estimated pharmacokineticprofile of a patient using a Bayesian model of pharmacokinetic profilesof sampled patients, the estimated pharmacokinetic profile based upon atleast one of a body weight or an age of the patient such that: a firstweighting factor is applied to the Bayesian model of pharmacokineticprofiles of sampled patients if the half-life of the patient is greaterthan the predetermined threshold, and a second weighting factor, lessthan the first weighting factor, is applied to the Bayesian model ofpharmacokinetic profiles of sampled patients if the half-life of thepatient is less than the predetermined threshold; determining, via theprocessor, a dosing regimen for a specified dosing interval including(i) a dosage and (ii) an estimated clotting factor VIII clearance forthe patient over a time period based at least upon the estimatedpharmacokinetic profile; and displaying the dosing regimen on a clientdevice.
 2. The method of claim 1, further comprising adjusting, via theprocessor, the estimated pharmacokinetic profile of the patient uponprevious treatments of the patient.
 3. The method of claim 1, whereinthe specified dosing interval is 48 hours or 72 hours.
 4. The method ofclaim 1, wherein the minimum threshold level is less than 20%.
 5. Themethod of claim 1, wherein the dosage is determined such that theestimated clotting factor VIII clearance in the patient over the timeperiod does not fall below the minimum threshold level.
 6. The method ofclaim 1, wherein the estimated clotting factor VIII clearance in thepatient is based upon at least one of a minimum threshold level, thedosage, or the specified dosing interval.
 7. The method of claim 1,wherein the Bayesian model includes a two-compartment model having afirst compartment corresponding to a time to metabolize the clottingfactor VIII and a second compartment corresponding to a dose forachieving a certain amount of the clotting factor VIII within thepatient.
 8. An apparatus for providing a therapeutic plasma proteindosing regimen to a client device, the apparatus comprising: a modelgenerator configured to create a Bayesian model of pharmacokineticprofiles of sampled patients, the Bayesian model including a (i)therapeutic plasma protein clearance and (ii) a volume of distributionrelationship for a therapeutic plasma protein based upon at least one ofpatient age or body weight; and a pharmacokinetic server configured to:determine an approximate pharmacokinetic profile of a patient based uponthe Bayesian model, a half-life of the therapeutic plasma protein withinthe patient, and at least one of an age of the patient or a weight ofthe patient; determine the therapeutic plasma protein dosing regimenincluding a dosage and a therapeutic plasma protein level over a timeperiod based upon the approximate pharmacokinetic profile of thepatient; modify the therapeutic plasma protein dosing regimen inresponse to receiving a dosing interval for applying the dosage to thepatient; and transmit the modified therapeutic plasma protein dosingregimen to the client device.
 9. The apparatus of claim 8, wherein thedosing interval is a two-day dosing interval, and wherein thepharmacokinetic server is configured to further modify the therapeuticplasma protein dosing regimen in response to receiving a three-daydosing interval in place of the two-day dosing interval.
 10. Theapparatus of claim 8, wherein the pharmacokinetic server is configuredto transmit a drug dosing tool to the client device, the drug dosingtool being configured to determine the therapeutic plasma protein dosingregimen and the modified therapeutic plasma protein dosing regimen. 11.The apparatus of claim 8, wherein the pharmacokinetic server is furtherconfigured to modify the therapeutic plasma protein dosing regimen basedon daily activities of the patient.
 12. The apparatus of claim 8,wherein the pharmacokinetic server is further configured to transmit themodified therapeutic plasma protein dosing regimen to an infusion pumpfor administering the therapeutic plasma protein to the patient.
 13. Theapparatus of claim 8, wherein the approximate pharmacokinetic profile isa first approximate pharmacokinetic profile determined for a firsttherapeutic plasma protein treatment of the patient, and wherein thepharmacokinetic server is further configured to determine a secondapproximate pharmacokinetic profile for the patient for a secondtherapeutic plasma protein treatment of the patient based on themodified therapeutic plasma protein dosing regimen.
 14. The apparatus ofclaim 8, wherein the volume of distribution relationship for thetherapeutic plasma protein is a relationship for at least one ofclotting factor VIII and modified forms of clotting factor VIII.
 15. Amachine-accessible device having instructions stored thereon that areconfigured, when executed, to cause a machine to at least: prompt a userto enter at least one of a patient weight or age; use a Bayesian modelof pharmacokinetic profiles of sampled patients to determine anapproximate pharmacokinetic profile of a patient based upon the Bayesianmodel, a half-life of the therapeutic plasma protein within the patient,and the at least one of entered patient weight or age, the Bayesianmodel including (i) a therapeutic plasma protein clearance and (ii) avolume of distribution relationship for a therapeutic plasma proteinbased upon the at least one of entered patient weight or age; determinea dosing regimen for the patient based upon the approximatepharmacokinetic profile of the patient, the dosing regimen including adosage and a dosage interval; modify the dosing regimen in response toreceiving another dosing interval for applying the dosage to thepatient; and enable the dosing regimen and a time-varying therapeuticplasma protein level based on the dosing regimen to be displayed to auser.
 16. The machine-accessible device of claim 15, further comprisinginstructions stored thereon that are configured when executed to causethe machine to: determine a first dosing regimen for a two-day dosinginterval; determine a second dosing regimen for a three-day dosinginterval; and enable the display of the first dosing regimen inconjunction with the second dosing regimen.
 17. The machine-accessibledevice of claim 15, further comprising instructions stored thereon thatare configured when executed to cause the machine to display a graphicalrepresentation of a time-varying amount of the therapeutic plasmaprotein within the patient, including at least one indication of a doseof the therapeutic plasma protein being provided to the patient.
 18. Themachine-accessible device of claim 15, further comprising instructionsstored thereon that are configured when executed to cause the machine todisplay a graphical feature than enables a user to change at least oneof: (i) a minimum concentration threshold; (ii) the dosage interval; or(iii) the dosage of the therapeutic plasma protein.
 19. Themachine-accessible device of claim 18, further comprising instructionsstored thereon that are configured when executed to cause the machine tomodify the dosing regimen in response to receiving a change of any oneof the items (i), (ii), or (iii).
 20. The machine-accessible device ofclaim 19, further comprising instructions stored thereon that areconfigured when executed to cause the machine to display a graphicalrepresentation of a change in the amount of the therapeutic plasmaprotein within the patient over time based on the change of any one ofthe items (i), (ii), or (iii).
 21. The machine-accessible device ofclaim 19, further comprising instructions stored thereon that areconfigured when executed to cause the machine to receive a minimumconcentration threshold and to display an amount of time the therapeuticplasma protein level is below the minimum concentration threshold. 22.The machine-accessible device of claim 15, further comprisinginstructions stored thereon that are configured when executed to causethe machine to: receive patient measurement blood data laboratoryincluding a concentration of the therapeutic plasma protein within thepatient after a time from when the therapeutic plasma protein wasadministered to the patient; and modify the approximate pharmacokineticprofile based on the patient measurement blood laboratory data.
 23. Adrug dosing tool, the tool comprising: interface circuits configured toreceive two blood samples collected from a patient after an infusion ofclotting factor VIII; one or more processors coupled to memory, the oneor more processors configured to: determine a first elimination rateconstant of clotting factor VIII for the patient based on the two bloodsamples; determine a second elimination rate constant using a Bayesianmodel of pharmacokinetic (PK) profiles of sampled patients each of whichare stored in the memory, wherein the second elimination rate isassociated an elimination rate of the clotting factor VIII of apopulation defined by the sampled patients, the population having asimilar age and body weight of the patient; determining a relationshipbetween the first elimination rate constant and the second eliminationrate constant and updating the Bayesian model based on the relationship;determine an estimated PK profile of the patient using the updatedBayesian model; determine a dosing regimen for a specified dosinginterval including (i) a dosage and (ii) an estimated clotting factorVIII clearance for the patient over a time period based at least uponthe estimated pharmacokinetic profile; and control an infusion pump foradministration of the clotting factor VIII based on the estimatedpharmacokinetic profile.